From d30e9831e6c17fc6b28383ae4592070ccd83657e Mon Sep 17 00:00:00 2001
From: willtanoe <willtanu86@gmail.com>
Date: Wed, 30 Sep 2026 22:03:46 +0700
Subject: [PATCH] experiment: complete two-dataset beta study

---
 ...a0.25__multiseed__audit_recomputation.json |   311 +
 ...lpha0.25__multiseed__beta0_equivalence.csv |     4 +
 ...5__multiseed__client_validation_deltas.csv |   151 +
 ...5__multiseed__client_validation_detail.csv |   151 +
 ...__multiseed__client_validation_summary.csv |    16 +
 ...25__multiseed__prototype_effect_pooled.csv |    46 +
 .../5gnidd__alpha0.25__multiseed__runtime.csv |    19 +
 ...pha0.25__multiseed__selection_summary.json |   111 +
 ...alpha0.25__multiseed__test_descriptive.csv |    19 +
 ...ha0.25__multiseed__validation_per_seed.csv |    16 +
 ...lpha0.25__multiseed__validation_pooled.csv |     6 +
 ..._alpha0.25__partition_characterization.csv |    31 +
 ...t_weighted__beta0__prototype_snapshot.json | 10527 ++++++++++++++++
 ...__prototype_snapshot__prototype_effect.csv |    46 +
 ..._prototype_snapshot__prototype_weights.csv |   401 +
 ...t_weighted__beta0__prototype_snapshot.json | 10527 ++++++++++++++++
 ...__prototype_snapshot__prototype_effect.csv |    46 +
 ..._prototype_snapshot__prototype_weights.csv |   401 +
 ...t_weighted__beta0__prototype_snapshot.json | 10527 ++++++++++++++++
 ...__prototype_snapshot__prototype_effect.csv |    46 +
 ..._prototype_snapshot__prototype_weights.csv |   401 +
 ...d__cross_alpha__cross_alpha_beta_table.csv |     5 +
 ...ross_alpha__cross_alpha_client_summary.csv |    15 +
 ..._cross_alpha__cross_alpha_displacement.csv |    45 +
 ...idd__cross_alpha__cross_alpha_summary.json |    22 +
 ..._cross_alpha__partition_heterogeneity.json |    94 +
 ...pha__partition_heterogeneity_per_class.csv |    27 +
 ...lpha__partition_heterogeneity_per_seed.csv |     3 +
 ...alpha__partition_heterogeneity_summary.csv |     1 +
 .../analysis/cross_dataset__beta_curve.csv    |    31 +
 .../cross_dataset__matched_alpha_summary.csv  |     7 +
 .../cross_dataset__matched_alpha_summary.json |   516 +
 docs/handoff/SESSION_HANDOFF.md               |   418 +-
 .../5GNIDD_ALPHA025_BETA_VALIDATION.md        |   460 +
 docs/research/5GNIDD_CROSS_ALPHA_ANALYSIS.md  |   262 +
 docs/research/CROSS_DATASET_BETA_ANALYSIS.md  |   240 +
 docs/research/SESSION11_AUDIT.md              |   284 +
 37 files changed, 36038 insertions(+), 195 deletions(-)
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__multiseed__audit_recomputation.json
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__multiseed__beta0_equivalence.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_deltas.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_detail.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_summary.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__multiseed__prototype_effect_pooled.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__multiseed__runtime.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__multiseed__selection_summary.json
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__multiseed__test_descriptive.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_per_seed.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_pooled.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__partition_characterization.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot.json
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot__prototype_effect.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot__prototype_weights.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot.json
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot__prototype_effect.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot__prototype_weights.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot.json
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot__prototype_effect.csv
 create mode 100644 artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot__prototype_weights.csv
 create mode 100644 artifacts/analysis/cross_dataset__beta_curve.csv
 create mode 100644 artifacts/analysis/cross_dataset__matched_alpha_summary.csv
 create mode 100644 artifacts/analysis/cross_dataset__matched_alpha_summary.json
 create mode 100644 docs/research/5GNIDD_ALPHA025_BETA_VALIDATION.md
 create mode 100644 docs/research/5GNIDD_CROSS_ALPHA_ANALYSIS.md
 create mode 100644 docs/research/CROSS_DATASET_BETA_ANALYSIS.md
 create mode 100644 docs/research/SESSION11_AUDIT.md

diff --git a/artifacts/analysis/5gnidd__alpha0.25__multiseed__audit_recomputation.json b/artifacts/analysis/5gnidd__alpha0.25__multiseed__audit_recomputation.json
new file mode 100644
index 0000000..0fbde43
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__multiseed__audit_recomputation.json
@@ -0,0 +1,311 @@
+{
+  "checks": [
+    {
+      "detail": "18/18 runs complete, config conformant",
+      "name": "run_inventory_18_full",
+      "ok": true
+    },
+    {
+      "detail": "",
+      "name": "snapshots_18_present",
+      "ok": true
+    },
+    {
+      "detail": "{\"0\": {\"manifest_content_hash\": \"ab6d8a8b63d478c4f6cfd88f96ccc7e16e1902f5e2c0ceac0f38ea26cfcda788\", \"round0_snapshot_sha256\": \"e2243ac4ed4391ff42ae358ab47ae4b98177227ac6e3ff0cdfd3a9147bf0d7c7\", \"unique_counts\": [1, 1, 1, 1, 1]}, \"1\": {\"manifest_content_hash\": \"74df102e4edb4509ba32b2625aa6a99f4bbd1dbbac0fc61d3bcccd50f21475ba\", \"round0_snapshot_sha256\": \"26a162991b7cbde947040c32c3d01b91841b6a58edc917038f813c8cbbd335b7\", \"unique_counts\": [1, 1, 1, 1, 1]}, \"2\": {\"manifest_content_hash\": \"061c094d1913f942267bdb5654d3c0d8cfef3fa592be6cd5a1845a5eb5cdc8f2\", \"round0_snapshot_sha256\": \"e287bff5ca71f8d2a677263ed17b67e909baaaada66cd9e1cb0c7f9e0c829b62\", \"unique_counts\": [1, 1, 1, 1, 1]}}",
+      "name": "pairing_within_seed",
+      "ok": true
+    },
+    {
+      "detail": "{\"0\": {\"content_hash\": \"ab6d8a8b63d478c4f6cfd88f96ccc7e16e1902f5e2c0ceac0f38ea26cfcda788\", \"partition_hash\": \"e628c17369f25e355cc8917f140e43f97e37ddc77e3193b6a1b0cbdc75a9ee12\", \"split_hash\": \"18f89f4807de5493e83cbc19a87df51268050c5fb3a12f286e64c3115073dea7\", \"reproduced_support_match\": true, \"reproduced_partition_hash_match\": true, \"sizes\": {\"test\": 243177, \"train\": 851123, \"validation\": 121589}}, \"1\": {\"content_hash\": \"74df102e4edb4509ba32b2625aa6a99f4bbd1dbbac0fc61d3bcccd50f21475ba\", \"partition_hash\": \"05aec12ceb4c94bda85b8baed5f4fa877017aa180c543c966eacbeb620397e0e\", \"split_hash\": \"3d05b7fe48d5a06ce5076eb60084349adc777872a54ddd566f7461f2f0c3579e\", \"reproduced_support_match\": true, \"reproduced_partition_hash_match\": true, \"sizes\": {\"test\": 243177, \"train\": 851123, \"validation\": 121589}}, \"2\": {\"content_hash\": \"061c094d1913f942267bdb5654d3c0d8cfef3fa592be6cd5a1845a5eb5cdc8f2\", \"partition_hash\": \"d9631ea6b2d3907e04389af8003ae7444fc50af30467d70853690cf5e87d5660\", \"split_hash\": \"fc758d060dc51dec113b118e07cda6a012b5bd825aa64fb515d595cd1684417f\", \"reproduced_support_match\": true, \"reproduced_partition_hash_match\": true, \"sizes\": {\"test\": 243177, \"train\": 851123, \"validation\": 121589}}}",
+      "name": "manifest_reproduced_from_raw",
+      "ok": true
+    },
+    {
+      "detail": "cells=1620 mismatches=0 benign_never_rare=True",
+      "name": "rare_unseen_integrity",
+      "ok": true
+    },
+    {
+      "detail": "max_per_client_mean_diff=0.00e+00 max_global_diff=0.00e+00",
+      "name": "validation_recomputation",
+      "ok": true
+    },
+    {
+      "detail": "recomputed_selected=0.0 summary_selected=0.0",
+      "name": "pooled_selection_recomputation",
+      "ok": true
+    },
+    {
+      "detail": "max_diff_vs_test_descriptive=0.00e+00; selected_beta=0.0",
+      "name": "test_selected_and_original_recompute",
+      "ok": true
+    },
+    {
+      "detail": "classifications=B,B,B",
+      "name": "beta0_equivalence",
+      "ok": true
+    },
+    {
+      "detail": "{\"5g_a025\": 0.0, \"5g_a050\": 1.0, \"5g_a075\": 0.5, \"xii_a025\": 0.0, \"xii_a050\": 0.75, \"xii_a075\": 0.5}",
+      "name": "cross_condition_labels",
+      "ok": true
+    },
+    {
+      "detail": "",
+      "name": "no_equal_available",
+      "ok": true
+    },
+    {
+      "detail": "",
+      "name": "only_18_alpha025_runs",
+      "ok": true
+    },
+    {
+      "detail": "",
+      "name": "no_5gnidd_alpha050_075_change",
+      "ok": true
+    },
+    {
+      "detail": "clean",
+      "name": "planningawal_unchanged",
+      "ok": true
+    },
+    {
+      "detail": "sha256 matched",
+      "name": "raw_datasets_unchanged",
+      "ok": true
+    }
+  ],
+  "cross_labels": {
+    "5g_a025": 0.0,
+    "5g_a050": 1.0,
+    "5g_a075": 0.5,
+    "xii_a025": 0.0,
+    "xii_a050": 0.75,
+    "xii_a075": 0.5
+  },
+  "manifest_reproduction": {
+    "0": {
+      "content_hash": "ab6d8a8b63d478c4f6cfd88f96ccc7e16e1902f5e2c0ceac0f38ea26cfcda788",
+      "partition_hash": "e628c17369f25e355cc8917f140e43f97e37ddc77e3193b6a1b0cbdc75a9ee12",
+      "reproduced_partition_hash_match": true,
+      "reproduced_support_match": true,
+      "sizes": {
+        "test": 243177,
+        "train": 851123,
+        "validation": 121589
+      },
+      "split_hash": "18f89f4807de5493e83cbc19a87df51268050c5fb3a12f286e64c3115073dea7"
+    },
+    "1": {
+      "content_hash": "74df102e4edb4509ba32b2625aa6a99f4bbd1dbbac0fc61d3bcccd50f21475ba",
+      "partition_hash": "05aec12ceb4c94bda85b8baed5f4fa877017aa180c543c966eacbeb620397e0e",
+      "reproduced_partition_hash_match": true,
+      "reproduced_support_match": true,
+      "sizes": {
+        "test": 243177,
+        "train": 851123,
+        "validation": 121589
+      },
+      "split_hash": "3d05b7fe48d5a06ce5076eb60084349adc777872a54ddd566f7461f2f0c3579e"
+    },
+    "2": {
+      "content_hash": "061c094d1913f942267bdb5654d3c0d8cfef3fa592be6cd5a1845a5eb5cdc8f2",
+      "partition_hash": "d9631ea6b2d3907e04389af8003ae7444fc50af30467d70853690cf5e87d5660",
+      "reproduced_partition_hash_match": true,
+      "reproduced_support_match": true,
+      "sizes": {
+        "test": 243177,
+        "train": 851123,
+        "validation": 121589
+      },
+      "split_hash": "fc758d060dc51dec113b118e07cda6a012b5bd825aa64fb515d595cd1684417f"
+    }
+  },
+  "pairing": {
+    "0": {
+      "manifest_content_hash": "ab6d8a8b63d478c4f6cfd88f96ccc7e16e1902f5e2c0ceac0f38ea26cfcda788",
+      "round0_snapshot_sha256": "e2243ac4ed4391ff42ae358ab47ae4b98177227ac6e3ff0cdfd3a9147bf0d7c7",
+      "unique_counts": [
+        1,
+        1,
+        1,
+        1,
+        1
+      ]
+    },
+    "1": {
+      "manifest_content_hash": "74df102e4edb4509ba32b2625aa6a99f4bbd1dbbac0fc61d3bcccd50f21475ba",
+      "round0_snapshot_sha256": "26a162991b7cbde947040c32c3d01b91841b6a58edc917038f813c8cbbd335b7",
+      "unique_counts": [
+        1,
+        1,
+        1,
+        1,
+        1
+      ]
+    },
+    "2": {
+      "manifest_content_hash": "061c094d1913f942267bdb5654d3c0d8cfef3fa592be6cd5a1845a5eb5cdc8f2",
+      "round0_snapshot_sha256": "e287bff5ca71f8d2a677263ed17b67e909baaaada66cd9e1cb0c7f9e0c829b62",
+      "unique_counts": [
+        1,
+        1,
+        1,
+        1,
+        1
+      ]
+    }
+  },
+  "pooled_recomputed": {
+    "0.0": 0.7614534210908004,
+    "0.25": 0.7492858468825278,
+    "0.5": 0.7257145491666086,
+    "0.75": 0.7222353067403979,
+    "1.0": 0.7376364240173013
+  },
+  "rare_unseen": {
+    "benign_never_rare": true,
+    "cells": 1620,
+    "mismatches": 0
+  },
+  "selected_beta": 0.0,
+  "test_recompute": {
+    "original_protean": {
+      "test_accuracy": {
+        "mean": 0.7309682522058693,
+        "std": 0.02143091560670625
+      },
+      "test_macro_f1": {
+        "mean": 0.8194054339450639,
+        "std": 0.013918675694370832
+      },
+      "test_rare_macro_f1": {
+        "mean": 0.842274405000354,
+        "std": 0.02537006851997817
+      },
+      "test_rare_recall": {
+        "mean": 0.9605557026664359,
+        "std": 0.032423277290702865
+      },
+      "test_weighted_f1": {
+        "mean": 0.7054354167590718,
+        "std": 0.02036694411653514
+      }
+    },
+    "support_weighted_beta0": {
+      "test_accuracy": {
+        "mean": 0.730225309136966,
+        "std": 0.019524710435296355
+      },
+      "test_macro_f1": {
+        "mean": 0.8166404182626198,
+        "std": 0.01335696520619808
+      },
+      "test_rare_macro_f1": {
+        "mean": 0.8412355814155769,
+        "std": 0.024201888695409735
+      },
+      "test_rare_recall": {
+        "mean": 0.9612162422875251,
+        "std": 0.03134699156678076
+      },
+      "test_weighted_f1": {
+        "mean": 0.7044634053674654,
+        "std": 0.018175165847202895
+      }
+    },
+    "support_weighted_beta0.25": {
+      "test_accuracy": {
+        "mean": 0.7267573276529715,
+        "std": 0.0337814569665739
+      },
+      "test_macro_f1": {
+        "mean": 0.810416876080481,
+        "std": 0.04867640473829211
+      },
+      "test_rare_macro_f1": {
+        "mean": 0.8293375964698669,
+        "std": 0.05275869099325297
+      },
+      "test_rare_recall": {
+        "mean": 0.950863093217594,
+        "std": 0.03944397658727933
+      },
+      "test_weighted_f1": {
+        "mean": 0.7009225427362763,
+        "std": 0.034629866318624726
+      }
+    },
+    "support_weighted_beta0.5": {
+      "test_accuracy": {
+        "mean": 0.6972287675232444,
+        "std": 0.04144983477868016
+      },
+      "test_macro_f1": {
+        "mean": 0.7505632677840134,
+        "std": 0.05068263163779094
+      },
+      "test_rare_macro_f1": {
+        "mean": 0.7644442375478815,
+        "std": 0.05406143308807409
+      },
+      "test_rare_recall": {
+        "mean": 0.9070376863722455,
+        "std": 0.07021524798343894
+      },
+      "test_weighted_f1": {
+        "mean": 0.6677402022784357,
+        "std": 0.04527229016167609
+      }
+    },
+    "support_weighted_beta0.75": {
+      "test_accuracy": {
+        "mean": 0.6955084842179428,
+        "std": 0.05407307332578784
+      },
+      "test_macro_f1": {
+        "mean": 0.7531777053479555,
+        "std": 0.05331479987191922
+      },
+      "test_rare_macro_f1": {
+        "mean": 0.7532847533313242,
+        "std": 0.06660609956244676
+      },
+      "test_rare_recall": {
+        "mean": 0.8825637715291018,
+        "std": 0.11211936093032276
+      },
+      "test_weighted_f1": {
+        "mean": 0.6761029448266797,
+        "std": 0.056097708494466936
+      }
+    },
+    "support_weighted_beta1": {
+      "test_accuracy": {
+        "mean": 0.7202490367098863,
+        "std": 0.04263132393724577
+      },
+      "test_macro_f1": {
+        "mean": 0.7823485391329442,
+        "std": 0.05061562466443954
+      },
+      "test_rare_macro_f1": {
+        "mean": 0.7817038465815722,
+        "std": 0.06268596968663277
+      },
+      "test_rare_recall": {
+        "mean": 0.8960473857848337,
+        "std": 0.08588546995533661
+      },
+      "test_weighted_f1": {
+        "mean": 0.7100951360498828,
+        "std": 0.04543070077476825
+      }
+    }
+  },
+  "validation": {
+    "max_global_diff": 0.0,
+    "max_per_client_mean_diff": 0.0
+  }
+}
diff --git a/artifacts/analysis/5gnidd__alpha0.25__multiseed__beta0_equivalence.csv b/artifacts/analysis/5gnidd__alpha0.25__multiseed__beta0_equivalence.csv
new file mode 100644
index 0000000..aa8f1e5
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__multiseed__beta0_equivalence.csv
@@ -0,0 +1,4 @@
+dataset,alpha,seed,same_manifest_content_hash,round0_snapshot_sha256_original,round0_snapshot_sha256_beta0,round0_snapshot_byte_identical,support_char_rare_identical,aggregation_max_abs_diff,history_rare_f1_round0_diff,history_rare_f1_max_diff_rounds_ge1,test_metric_max_abs_diff,classification
+5gnidd,0.25,0,True,e2243ac4ed4391ff42ae358ab47ae4b98177227ac6e3ff0cdfd3a9147bf0d7c7,e2243ac4ed4391ff42ae358ab47ae4b98177227ac6e3ff0cdfd3a9147bf0d7c7,True,True,4.440892098500626e-16,0.0,0.02174111227427633,0.005363118344290818,B
+5gnidd,0.25,1,True,26a162991b7cbde947040c32c3d01b91841b6a58edc917038f813c8cbbd335b7,26a162991b7cbde947040c32c3d01b91841b6a58edc917038f813c8cbbd335b7,True,True,4.440892098500626e-16,0.0,0.06854095251486358,0.005385720515183823,B
+5gnidd,0.25,2,True,e287bff5ca71f8d2a677263ed17b67e909baaaada66cd9e1cb0c7f9e0c829b62,e287bff5ca71f8d2a677263ed17b67e909baaaada66cd9e1cb0c7f9e0c829b62,True,True,6.661338147750939e-16,0.0,0.027399918376093346,0.0028532236723721738,B
diff --git a/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_deltas.csv b/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_deltas.csv
new file mode 100644
index 0000000..a351ab1
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_deltas.csv
@@ -0,0 +1,151 @@
+seed,beta,client_id,n_samples,val_rare_macro_f1,val_rare_recall
+0,0.0,0,629,0.7205774853801169,0.9967213114754099
+0,0.0,1,5107,0.9591792028969309,0.9606197836208497
+0,0.0,2,29612,0.0,0.0
+0,0.0,3,36305,0.9424363245858006,1.0
+0,0.0,4,27425,0.6713685142161743,0.9974554707379135
+0,0.0,5,7976,0.5061793112212479,0.9682119205298013
+0,0.0,6,6702,0.5739818472345016,0.986848635235732
+0,0.0,7,230,0.9898785425101214,0.9801587301587302
+0,0.0,8,6655,1.0,1.0
+0,0.0,9,948,1.0,1.0
+0,0.25,0,629,0.6983552631578946,0.9967213114754099
+0,0.25,1,5107,0.9479293854293854,0.9422373284966159
+0,0.25,2,29612,0.0,0.0
+0,0.25,3,36305,0.9662458483953245,1.0
+0,0.25,4,27425,0.8607755880483152,0.9974554707379135
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_detail.csv b/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_detail.csv
new file mode 100644
index 0000000..604db5f
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_detail.csv
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_summary.csv b/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_summary.csv
new file mode 100644
index 0000000..9c776db
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_summary.csv
@@ -0,0 +1,16 @@
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__multiseed__prototype_effect_pooled.csv b/artifacts/analysis/5gnidd__alpha0.25__multiseed__prototype_effect_pooled.csv
new file mode 100644
index 0000000..1daf540
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__multiseed__prototype_effect_pooled.csv
@@ -0,0 +1,46 @@
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__multiseed__runtime.csv b/artifacts/analysis/5gnidd__alpha0.25__multiseed__runtime.csv
new file mode 100644
index 0000000..96c2cdb
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__multiseed__runtime.csv
@@ -0,0 +1,19 @@
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__multiseed__selection_summary.json b/artifacts/analysis/5gnidd__alpha0.25__multiseed__selection_summary.json
new file mode 100644
index 0000000..dad43f0
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__multiseed__selection_summary.json
@@ -0,0 +1,111 @@
+{
+  "alpha": 0.25,
+  "betas": [
+    0.0,
+    0.25,
+    0.5,
+    0.75,
+    1.0
+  ],
+  "dataset": "5gnidd",
+  "missing_artifacts": [],
+  "n_missing_artifacts": 0,
+  "outputs": {
+    "client_deltas": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_deltas.csv",
+    "client_validation_detail": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_detail.csv",
+    "client_validation_summary": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/5gnidd__alpha0.25__multiseed__client_validation_summary.csv",
+    "per_seed": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_per_seed.csv",
+    "pooled": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_pooled.csv",
+    "prototype_effect_pooled": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/5gnidd__alpha0.25__multiseed__prototype_effect_pooled.csv",
+    "test_descriptive": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/5gnidd__alpha0.25__multiseed__test_descriptive.csv"
+  },
+  "per_seed_diagnostic": [
+    {
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+      "test_used_for_selection": false,
+      "val_rare_macro_f1_per_client_mean": 0.7472986688172722
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+      "selected_beta": 0.0,
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+    {
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+      "val_rare_macro_f1_per_client_mean": 0.7767324599762028
+    }
+  ],
+  "pooled_table": [
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+      "pooled_val_rare_macro_f1_per_client_mean": 0.7614534210908004,
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+      "pooled_val_rare_recall_per_client_mean": 0.9085770977445251,
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+      "n_seeds": 3,
+      "pooled_val_rare_macro_f1_per_client_mean": 0.7376364240173013,
+      "pooled_val_rare_recall_global": 0.8953098133708983,
+      "pooled_val_rare_recall_per_client_mean": 0.8889910199323897,
+      "std_pop_val_rare_macro_f1": 0.0022501360251623035,
+      "std_sample_val_rare_macro_f1": 0.002755842556750987
+    }
+  ],
+  "primary_selection": {
+    "rule": "max pooled validation per-client-mean rare-class macro-F1 (tie-break: recall, then lower std, then smaller beta)",
+    "selected_beta": 0.0,
+    "selection_split": "validation",
+    "test_used_for_selection": false,
+    "tie_break_used": false
+  },
+  "seeds": [
+    0,
+    1,
+    2
+  ]
+}
diff --git a/artifacts/analysis/5gnidd__alpha0.25__multiseed__test_descriptive.csv b/artifacts/analysis/5gnidd__alpha0.25__multiseed__test_descriptive.csv
new file mode 100644
index 0000000..d5b107b
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__multiseed__test_descriptive.csv
@@ -0,0 +1,19 @@
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_per_seed.csv b/artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_per_seed.csv
new file mode 100644
index 0000000..8d2c91a
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_per_seed.csv
@@ -0,0 +1,16 @@
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_pooled.csv b/artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_pooled.csv
new file mode 100644
index 0000000..67ad757
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_pooled.csv
@@ -0,0 +1,6 @@
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__partition_characterization.csv b/artifacts/analysis/5gnidd__alpha0.25__partition_characterization.csv
new file mode 100644
index 0000000..a1af124
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__partition_characterization.csv
@@ -0,0 +1,31 @@
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot.json b/artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot.json
new file mode 100644
index 0000000..07fd8b5
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot.json
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+}
diff --git a/artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot__prototype_effect.csv b/artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot__prototype_effect.csv
new file mode 100644
index 0000000..701d5a4
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot__prototype_effect.csv
@@ -0,0 +1,46 @@
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot__prototype_weights.csv b/artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot__prototype_weights.csv
new file mode 100644
index 0000000..7a28872
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot__prototype_weights.csv
@@ -0,0 +1,401 @@
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot.json b/artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot.json
new file mode 100644
index 0000000..dcfa37a
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot.json
@@ -0,0 +1,10527 @@
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot__prototype_effect.csv b/artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot__prototype_effect.csv
new file mode 100644
index 0000000..083990a
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot__prototype_effect.csv
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot__prototype_weights.csv b/artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot__prototype_weights.csv
new file mode 100644
index 0000000..7930cf1
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__seed1__support_weighted__beta0__prototype_snapshot__prototype_weights.csv
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot.json b/artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot.json
new file mode 100644
index 0000000..aee1c23
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot.json
@@ -0,0 +1,10527 @@
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot__prototype_effect.csv b/artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot__prototype_effect.csv
new file mode 100644
index 0000000..01c0130
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot__prototype_effect.csv
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diff --git a/artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot__prototype_weights.csv b/artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot__prototype_weights.csv
new file mode 100644
index 0000000..b1a16e7
--- /dev/null
+++ b/artifacts/analysis/5gnidd__alpha0.25__seed2__support_weighted__beta0__prototype_snapshot__prototype_weights.csv
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+7,UDPFlood,1.0,2,113.0,0.00035297278048841436
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+7,UDPFlood,1.0,4,4837.0,0.015109109196658942
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+8,UDPScan,0.0,0,3899.0,0.14285714285714285
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+8,UDPScan,0.25,5,1018.0,0.13736197566765845
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+8,UDPScan,0.25,7,1184.0,0.14264859869122043
+8,UDPScan,0.25,9,3407.0,0.1857901209757188
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+8,UDPScan,0.5,2,436.0,0.08208777629829044
+8,UDPScan,0.5,4,243.0,0.06128276942677685
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+8,UDPScan,0.75,0,3899.0,0.2992044352196282
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+8,UDPScan,0.75,4,243.0,0.037321389612737614
+8,UDPScan,0.75,5,1018.0,0.10928584989955037
+8,UDPScan,0.75,6,947.0,0.10351793137900643
+8,UDPScan,0.75,7,1184.0,0.12239590203744032
+8,UDPScan,0.75,9,3407.0,0.2704158856352494
+8,UDPScan,1.0,0,3899.0,0.3501886114603916
+8,UDPScan,1.0,2,436.0,0.039159331776540324
+8,UDPScan,1.0,4,243.0,0.021825040416741513
+8,UDPScan,1.0,5,1018.0,0.09143165079935334
+8,UDPScan,1.0,6,947.0,0.0850547871384947
+8,UDPScan,1.0,7,1184.0,0.1063409376684031
+8,UDPScan,1.0,9,3407.0,0.30599964074007546
diff --git a/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_beta_table.csv b/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_beta_table.csv
index 448a4fe..9e80351 100644
--- a/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_beta_table.csv
+++ b/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_beta_table.csv
@@ -1,4 +1,9 @@
 dataset,alpha,beta,n_seeds,pooled_val_mean,pooled_val_std_sample,pooled_val_std_pop,pooled_val_min,pooled_val_max,pooled_val_recall,selected,cells_sj_lt_M_total,cells_total,missing_client_class_cells_total,client_size_ratio_mean,support_cv_mean,union_unseen_mean,mean_displacement_beta1
+5gnidd,0.25,0.0,3,0.7614534210908004,0.021902537932118035,0.017883347335214204,0.7363601228044894,0.7767324599762028,0.9085770977445251,True,16,27,30,17.600940070872678,1.3021194271854393,5.333333333333333,2.91943348262683
+5gnidd,0.25,0.25,3,0.7492858468825278,0.017106975874172658,0.013967787311275074,0.7332592430237032,0.7672996288066082,0.9071367963077813,False,16,27,30,17.600940070872678,1.3021194271854393,5.333333333333333,2.91943348262683
+5gnidd,0.25,0.5,3,0.7257145491666086,0.01101731431676257,0.008995599470642724,0.7174503698309587,0.7382227190445022,0.8949473995819205,False,16,27,30,17.600940070872678,1.3021194271854393,5.333333333333333,2.91943348262683
+5gnidd,0.25,0.75,3,0.7222353067403979,0.007966771094060871,0.00650484135933454,0.713262253662401,0.7284775896718815,0.8797107780157537,False,16,27,30,17.600940070872678,1.3021194271854393,5.333333333333333,2.91943348262683
+5gnidd,0.25,1.0,3,0.7376364240173013,0.002755842556750987,0.0022501360251623035,0.7344552755726921,0.7392969205366235,0.8889910199323897,False,16,27,30,17.600940070872678,1.3021194271854393,5.333333333333333,2.91943348262683
 5gnidd,0.5,0.0,3,0.6872301309573783,0.052725844344546816,0.04305047163384996,0.6332434333373904,0.7385974827605487,0.9477370387940001,False,4,27,4,9.594308791178781,1.2251708481787265,1.3333333333333333,2.3399083587182736
 5gnidd,0.5,0.25,3,0.6450777370820986,0.06474313739822393,0.052862550324183834,0.5737166466423315,0.7000551711341446,0.9468616498164765,False,4,27,4,9.594308791178781,1.2251708481787265,1.3333333333333333,2.3399083587182736
 5gnidd,0.5,0.5,3,0.6746687817772702,0.10225286523806497,0.08348911485694357,0.5633883995024869,0.7644872677811037,0.9436587867425653,False,4,27,4,9.594308791178781,1.2251708481787265,1.3333333333333333,2.3399083587182736
diff --git a/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_client_summary.csv b/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_client_summary.csv
index 144855c..649a1a4 100644
--- a/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_client_summary.csv
+++ b/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_client_summary.csv
@@ -1,4 +1,19 @@
 dataset,alpha,seed,beta,n_eligible,n_improve,n_degrade,n_unchanged,mean_delta,min_delta,max_delta
+5gnidd,0.25,0,0.0,10,0,0,10,0.0,0.0,0.0
+5gnidd,0.25,0,0.25,10,3,3,4,0.010938546012782963,-0.07653222666610299,0.18940707383214095
+5gnidd,0.25,0,0.5,10,3,4,3,-0.01890975297353068,-0.10737418541550403,0.023843748084083516
+5gnidd,0.25,0,0.75,10,3,4,3,-0.023097869142088355,-0.14782686599098172,0.08120187997137751
+5gnidd,0.25,0,1.0,10,3,4,3,-0.0019048472317972909,-0.1484580166381656,0.2777777777777778
+5gnidd,0.25,1,0.0,10,0,0,10,0.0,0.0,0.0
+5gnidd,0.25,1,0.25,10,3,3,4,-0.003968051685100719,-0.035080645161290336,0.006988021376510556
+5gnidd,0.25,1,0.5,10,2,4,4,-0.03304496144720663,-0.31650978982621863,0.0007581492441447457
+5gnidd,0.25,1,0.75,10,2,5,3,-0.04279009081982739,-0.4057158717743099,0.05971472095277662
+5gnidd,0.25,1,1.0,10,3,4,3,-0.0319707599550853,-0.3007384916695693,0.05547720837266114
+5gnidd,0.25,2,0.0,10,0,0,10,0.0,0.0,0.0
+5gnidd,0.25,2,0.25,10,0,4,6,-0.04347321695249963,-0.20521276595744675,0.0
+5gnidd,0.25,2,0.5,10,1,3,6,-0.05526190135183806,-0.2831161695447409,0.002564102564102555
+5gnidd,0.25,2,0.75,10,1,4,5,-0.05176638308929169,-0.26831675979891445,0.09614699026463747
+5gnidd,0.25,2,1.0,10,4,3,3,-0.03757538403361462,-0.2684826405938592,0.1510489510489511
 5gnidd,0.5,0,0.0,10,0,0,10,0.0,0.0,0.0
 5gnidd,0.5,0,0.25,10,2,7,1,-0.07713608929072921,-0.20363636363636362,0.030406580954845275
 5gnidd,0.5,0,0.5,10,7,2,1,0.025889785020554917,-0.03433523137896821,0.06985074626865678
diff --git a/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_displacement.csv b/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_displacement.csv
index 4a1a8b6..b4c04c0 100644
--- a/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_displacement.csv
+++ b/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_displacement.csv
@@ -1,4 +1,49 @@
 dataset,alpha,class_id,class_name,beta,n_seeds,mean_displacement,std_sample_displacement,mean_relative_displacement
+5gnidd,0.25,0,Benign,0.0,3,0.0,0.0,0.0
+5gnidd,0.25,0,Benign,0.25,3,1.3208867894419398,0.4046228465947186,0.23983953261805913
+5gnidd,0.25,0,Benign,0.5,3,1.8727315927020307,0.4620649789517894,0.3404401554383467
+5gnidd,0.25,0,Benign,0.75,3,2.28489006476199,0.4920344898577957,0.4157898773092243
+5gnidd,0.25,0,Benign,1.0,3,2.648344737773736,0.5188602564457683,0.4821737572132332
+5gnidd,0.25,1,HTTPFlood,0.0,3,0.0,0.0,0.0
+5gnidd,0.25,1,HTTPFlood,0.25,3,2.203804871336226,0.8752478432915377,0.3276588540398691
+5gnidd,0.25,1,HTTPFlood,0.5,3,3.135496752702504,1.2294222020173649,0.4648502648708635
+5gnidd,0.25,1,HTTPFlood,0.75,3,3.5467901328136713,1.4218932038360563,0.5260714573849847
+5gnidd,0.25,1,HTTPFlood,1.0,3,3.7602841668463944,1.5390234836296783,0.5584139964274445
+5gnidd,0.25,2,ICMPFlood,0.0,3,0.0,0.0,0.0
+5gnidd,0.25,2,ICMPFlood,0.25,3,0.4029121925023258,0.03218898834492902,0.11510871142077754
+5gnidd,0.25,2,ICMPFlood,0.5,3,0.7402981676160462,0.06302350856873123,0.21141829389362196
+5gnidd,0.25,2,ICMPFlood,0.75,3,1.0088940328474096,0.10943512225119882,0.2880600622121033
+5gnidd,0.25,2,ICMPFlood,1.0,3,1.2149615886933787,0.1507085895098706,0.34685106134597526
+5gnidd,0.25,3,SYNFlood,0.0,3,0.0,0.0,0.0
+5gnidd,0.25,3,SYNFlood,0.25,3,0.9255896141142367,0.5134034722569449,0.2677962234856806
+5gnidd,0.25,3,SYNFlood,0.5,3,1.7760206329532042,0.8152985107527552,0.5134951556701836
+5gnidd,0.25,3,SYNFlood,0.75,3,2.536161711310303,0.9547281136087009,0.7326178888273117
+5gnidd,0.25,3,SYNFlood,1.0,3,3.1763695442454467,1.0069739670231537,0.9167291408106705
+5gnidd,0.25,4,SYNScan,0.0,3,0.0,0.0,0.0
+5gnidd,0.25,4,SYNScan,0.25,3,1.5082484997446013,0.6622429474820746,0.21512110484443236
+5gnidd,0.25,4,SYNScan,0.5,3,2.532644317612205,1.005483400929481,0.3612738214093841
+5gnidd,0.25,4,SYNScan,0.75,3,3.270199976504887,1.2378832181008719,0.4665432178395166
+5gnidd,0.25,4,SYNScan,1.0,3,3.814579780422797,1.4018369744978139,0.5442267347415422
+5gnidd,0.25,5,SlowrateDoS,0.0,3,0.0,0.0,0.0
+5gnidd,0.25,5,SlowrateDoS,0.25,3,1.564877309272502,0.9738544836723891,0.2820388998650987
+5gnidd,0.25,5,SlowrateDoS,0.5,3,2.3857836065060547,1.203619044944969,0.4262312254284213
+5gnidd,0.25,5,SlowrateDoS,0.75,3,2.8594065609443517,1.1978680905380645,0.5076045381663238
+5gnidd,0.25,5,SlowrateDoS,1.0,3,3.178870743072719,1.1570108600313702,0.5619090743749164
+5gnidd,0.25,6,TCPConnectScan,0.0,3,0.0,0.0,0.0
+5gnidd,0.25,6,TCPConnectScan,0.25,3,1.3521264468297787,0.712355658772999,0.36317633423666756
+5gnidd,0.25,6,TCPConnectScan,0.5,3,2.3161305308289326,1.5604787814943968,0.6272116346725974
+5gnidd,0.25,6,TCPConnectScan,0.75,3,2.9159246182720526,2.201020849029129,0.7928641384888375
+5gnidd,0.25,6,TCPConnectScan,1.0,3,3.257943080113345,2.5741100653263422,0.8873673593640223
+5gnidd,0.25,7,UDPFlood,0.0,3,0.0,0.0,0.0
+5gnidd,0.25,7,UDPFlood,0.25,3,1.308343495852911,0.5667070359112721,0.2616291006327561
+5gnidd,0.25,7,UDPFlood,0.5,3,1.8907793895474538,0.6874579758805816,0.3770492970638934
+5gnidd,0.25,7,UDPFlood,0.75,3,2.2054121762177554,0.663497410401604,0.4382592556604308
+5gnidd,0.25,7,UDPFlood,1.0,3,2.4077369723424735,0.5783305176966848,0.47667894621080914
+5gnidd,0.25,8,UDPScan,0.0,3,0.0,0.0,0.0
+5gnidd,0.25,8,UDPScan,0.25,3,1.0718983781078881,0.8786656072524274,0.1454094837882409
+5gnidd,0.25,8,UDPScan,0.5,3,1.8488403956684099,1.3650411843943164,0.24853648413924292
+5gnidd,0.25,8,UDPScan,0.75,3,2.3990133237335334,1.555826676516962,0.31927389800074496
+5gnidd,0.25,8,UDPScan,1.0,3,2.815810730131176,1.6041886744624576,0.37142192996652196
 5gnidd,0.5,0,Benign,0.0,3,0.0,0.0,0.0
 5gnidd,0.5,0,Benign,0.25,3,0.6924394499491665,0.25819336974901685,0.12106050864023522
 5gnidd,0.5,0,Benign,0.5,3,1.1573935905937274,0.451235376777221,0.20253682870439962
diff --git a/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_summary.json b/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_summary.json
index 50209b6..daa5edf 100644
--- a/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_summary.json
+++ b/artifacts/analysis/5gnidd__cross_alpha__cross_alpha_summary.json
@@ -1,5 +1,27 @@
 {
   "alphas": {
+    "0.25": {
+      "cells_sj_lt_M_total": 16,
+      "cells_total": 27,
+      "client_size_ratio_mean": 17.600940070872678,
+      "mean_displacement_beta1": 2.91943348262683,
+      "missing_client_class_cells_total": 30,
+      "pooled_val_mean_range": [
+        0.7222353067403979,
+        0.7614534210908004
+      ],
+      "pooled_val_std_sample_range": [
+        0.002755842556750987,
+        0.021902537932118035
+      ],
+      "selected_beta": 0.0,
+      "selection_rule": "max pooled validation per-client-mean rare-class macro-F1 (tie-break: recall, then lower std, then smaller beta)",
+      "support_cv_mean": 1.3021194271854393,
+      "test_descriptive_present": true,
+      "test_used_for_selection": false,
+      "tie_break_used": false,
+      "union_unseen_mean": 5.333333333333333
+    },
     "0.5": {
       "cells_sj_lt_M_total": 4,
       "cells_total": 27,
diff --git a/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity.json b/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity.json
index c4f24fc..6a0a4ba 100644
--- a/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity.json
+++ b/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity.json
@@ -1,5 +1,6 @@
 {
   "alphas": [
+    0.25,
     0.5,
     0.75
   ],
@@ -7,6 +8,84 @@
   "per_class": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_per_class.csv",
   "per_seed": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_per_seed.csv",
   "per_seed_rows": [
+    {
+      "alpha": 0.25,
+      "client_size_max": 237693,
+      "client_size_min": 23943,
+      "client_size_ratio": 9.927452700162887,
+      "dataset": "5gnidd",
+      "manifest_content_hash": "ab6d8a8b63d478c4f6cfd88f96ccc7e16e1902f5e2c0ceac0f38ea26cfcda788",
+      "max_unseen_on_client": 3,
+      "n_cells_sj_lt_M": 6,
+      "n_class_condition_cells": 9,
+      "n_clients_2_rare": 10,
+      "n_missing_client_class_cells": 10,
+      "nij_sum": 851123,
+      "num_classes": 9,
+      "num_clients": 10,
+      "num_train": 851123,
+      "partition_hash": "e628c17369f25e355cc8917f140e43f97e37ddc77e3193b6a1b0cbdc75a9ee12",
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+      "split_hash": "18f89f4807de5493e83cbc19a87df51268050c5fb3a12f286e64c3115073dea7",
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+      "support_max_min_ratio_max": 185504.0,
+      "union_rare_count": 6,
+      "union_unseen_count": 6
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+      "client_size_max": 205900,
+      "client_size_min": 7399,
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+      "dataset": "5gnidd",
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+      "n_class_condition_cells": 9,
+      "n_clients_2_rare": 10,
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+      "nij_sum": 851123,
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+      "num_train": 851123,
+      "partition_hash": "05aec12ceb4c94bda85b8baed5f4fa877017aa180c543c966eacbeb620397e0e",
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+      "seed": 1,
+      "split_hash": "3d05b7fe48d5a06ce5076eb60084349adc777872a54ddd566f7461f2f0c3579e",
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+      "support_max_min_ratio_max": 128338.0,
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+      "union_unseen_count": 5
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+    {
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+      "client_size_max": 298192,
+      "client_size_min": 19817,
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+      "dataset": "5gnidd",
+      "manifest_content_hash": "061c094d1913f942267bdb5654d3c0d8cfef3fa592be6cd5a1845a5eb5cdc8f2",
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+      "n_missing_client_class_cells": 10,
+      "nij_sum": 851123,
+      "num_classes": 9,
+      "num_clients": 10,
+      "num_train": 851123,
+      "partition_hash": "d9631ea6b2d3907e04389af8003ae7444fc50af30467d70853690cf5e87d5660",
+      "rng_seed": 218373793,
+      "seed": 2,
+      "split_hash": "fc758d060dc51dec113b118e07cda6a012b5bd825aa64fb515d595cd1684417f",
+      "support_cv_max": 2.098823873342716,
+      "support_cv_mean": 1.3270685186489053,
+      "support_max_min_ratio_max": 22746.8,
+      "union_rare_count": 8,
+      "union_unseen_count": 5
+    },
     {
       "alpha": 0.5,
       "client_size_max": 178993,
@@ -171,6 +250,21 @@
   ],
   "summary": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_summary.csv",
   "summary_rows": [
+    {
+      "alpha": 0.25,
+      "cells_sj_lt_M_total": 16,
+      "cells_total": 27,
+      "client_size_ratio_max": 27.82808487633464,
+      "client_size_ratio_mean": 17.600940070872678,
+      "dataset": "5gnidd",
+      "max_unseen_on_client": 3,
+      "missing_client_class_cells_total": 30,
+      "n_seeds": 3,
+      "support_cv_mean": 1.3021194271854393,
+      "support_max_min_ratio_max": 185504.0,
+      "union_rare_mean": 6.666666666666667,
+      "union_unseen_mean": 5.333333333333333
+    },
     {
       "alpha": 0.5,
       "cells_sj_lt_M_total": 4,
diff --git a/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_per_class.csv b/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_per_class.csv
index 6e2d19a..079a4e3 100644
--- a/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_per_class.csv
+++ b/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_per_class.csv
@@ -1,4 +1,31 @@
 dataset,alpha,seed,class_id,class_name,total,num_clients,n_missing_clients,min,max,mean,std,cv,max_min_ratio
+5gnidd,0.25,0,0,Benign,334415,10,0,1,185504,33441.5,54297.395750164666,1.6236531181365867,185504.0
+5gnidd,0.25,0,1,HTTPFlood,98569,9,1,1,48469,10952.111111111111,15619.095146962789,1.4261264324753735,48469.0
+5gnidd,0.25,0,2,ICMPFlood,808,9,1,2,319,89.77777777777777,99.11360236031938,1.1039881451025675,159.5
+5gnidd,0.25,0,3,SYNFlood,6805,7,3,144,4762,972.1428571428571,1553.4714516270997,1.5979867981469065,33.06944444444444
+5gnidd,0.25,0,4,SYNScan,14030,7,3,237,6524,2004.2857142857142,2116.5558758299308,1.0560150485252684,27.52742616033755
+5gnidd,0.25,0,5,SlowrateDoS,51187,9,1,1,16517,5687.444444444444,6406.6724611682275,1.1264589085219694,16517.0
+5gnidd,0.25,0,6,TCPConnectScan,14037,9,1,2,10870,1559.6666666666667,3336.037403200923,2.138942553879626,5435.0
+5gnidd,0.25,0,7,UDPFlood,320138,10,0,1,127301,32013.8,44285.809189400614,1.3833349739612484,127301.0
+5gnidd,0.25,0,8,UDPScan,11134,10,0,2,4601,1113.4,1669.91060838597,1.4998298979575801,2300.5
+5gnidd,0.25,1,0,Benign,334415,10,0,30,177603,33441.5,50907.30907492558,1.5222794753502558,5920.1
+5gnidd,0.25,1,1,HTTPFlood,98569,9,1,5,45645,10952.111111111111,15449.722071893897,1.4106615532981472,9129.0
+5gnidd,0.25,1,2,ICMPFlood,808,10,0,1,257,80.8,94.58308516854375,1.1705827372344524,257.0
+5gnidd,0.25,1,3,SYNFlood,6805,9,1,10,2997,756.1111111111111,936.8245945680835,1.2390038723163486,299.7
+5gnidd,0.25,1,4,SYNScan,14030,10,0,7,3477,1403.0,1296.782711174081,0.9242927378289957,496.7142857142857
+5gnidd,0.25,1,5,SlowrateDoS,51187,8,2,211,23478,6398.375,7648.639175328837,1.1954033915375133,111.27014218009478
+5gnidd,0.25,1,6,TCPConnectScan,14037,8,2,36,3627,1754.625,1056.293039063971,0.6020050090839758,100.75
+5gnidd,0.25,1,7,UDPFlood,320138,10,0,1,128338,32013.8,41188.815061373156,1.2865956263040674,128338.0
+5gnidd,0.25,1,8,UDPScan,11134,6,4,67,5172,1855.6666666666667,1682.0645713593226,0.9064475865058321,77.19402985074628
+5gnidd,0.25,2,0,Benign,334415,10,0,10,227468,33441.5,65962.28801709352,1.972467981911503,22746.8
+5gnidd,0.25,2,1,HTTPFlood,98569,7,3,43,36762,14081.285714285714,13455.260572029978,0.9555420467308164,854.9302325581396
+5gnidd,0.25,2,2,ICMPFlood,808,8,2,6,355,101.0,118.30574795841494,1.1713440391922272,59.166666666666664
+5gnidd,0.25,2,3,SYNFlood,6805,9,1,3,3136,756.1111111111111,1064.1515602628585,1.4074010348810768,1045.3333333333333
+5gnidd,0.25,2,4,SYNScan,14030,10,0,2,10072,1403.0,2944.64989429983,2.098823873342716,5036.0
+5gnidd,0.25,2,5,SlowrateDoS,51187,10,0,4,31740,5118.7,9212.276190497112,1.7997296560644525,7935.0
+5gnidd,0.25,2,6,TCPConnectScan,14037,9,1,3,3619,1559.6666666666667,1403.3240696448004,0.8997589675004063,1206.3333333333333
+5gnidd,0.25,2,7,UDPFlood,320138,10,0,113,82051,32013.8,25362.204812673524,0.7922272523934529,726.1150442477876
+5gnidd,0.25,2,8,UDPScan,11134,7,3,243,3899,1590.5714285714287,1346.1352996255464,0.8463218158234977,16.045267489711936
 5gnidd,0.5,0,0,Benign,334415,10,0,226,108257,33441.5,35759.58709842718,1.0693176770906563,479.0132743362832
 5gnidd,0.5,0,1,HTTPFlood,98569,10,0,185,61393,9856.9,17538.944828295687,1.7793570826827592,331.8540540540541
 5gnidd,0.5,0,2,ICMPFlood,808,9,1,8,243,89.77777777777777,72.6342095369787,0.8090444131594163,30.375
diff --git a/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_per_seed.csv b/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_per_seed.csv
index b3c6deb..bbb1698 100644
--- a/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_per_seed.csv
+++ b/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_per_seed.csv
@@ -1,4 +1,7 @@
 dataset,alpha,seed,num_clients,num_classes,num_train,nij_sum,n_class_condition_cells,n_cells_sj_lt_M,n_missing_client_class_cells,client_size_min,client_size_max,client_size_ratio,union_rare_count,union_unseen_count,max_unseen_on_client,n_clients_2_rare,support_cv_mean,support_cv_max,support_max_min_ratio_max,manifest_content_hash,partition_hash,split_hash,rng_seed
+5gnidd,0.25,0,10,9,851123,851123,9,6,10,23943,237693,9.927452700162887,6,6,3,10,1.4395928751896807,2.138942553879626,185504.0,ab6d8a8b63d478c4f6cfd88f96ccc7e16e1902f5e2c0ceac0f38ea26cfcda788,e628c17369f25e355cc8917f140e43f97e37ddc77e3193b6a1b0cbdc75a9ee12,18f89f4807de5493e83cbc19a87df51268050c5fb3a12f286e64c3115073dea7,708356900
+5gnidd,0.25,1,10,9,851123,851123,9,5,10,7399,205900,27.82808487633464,6,5,3,10,1.139696887717732,1.5222794753502558,128338.0,74df102e4edb4509ba32b2625aa6a99f4bbd1dbbac0fc61d3bcccd50f21475ba,05aec12ceb4c94bda85b8baed5f4fa877017aa180c543c966eacbeb620397e0e,3d05b7fe48d5a06ce5076eb60084349adc777872a54ddd566f7461f2f0c3579e,902143161
+5gnidd,0.25,2,10,9,851123,851123,9,5,10,19817,298192,15.047282636120503,8,5,2,10,1.3270685186489053,2.098823873342716,22746.8,061c094d1913f942267bdb5654d3c0d8cfef3fa592be6cd5a1845a5eb5cdc8f2,d9631ea6b2d3907e04389af8003ae7444fc50af30467d70853690cf5e87d5660,fc758d060dc51dec113b118e07cda6a012b5bd825aa64fb515d595cd1684417f,218373793
 5gnidd,0.5,0,10,9,851123,851123,9,2,2,15388,178993,11.631985963088121,6,2,1,10,1.224175005199598,1.7831313104092381,88943.0,0732582cf4510089212717816d2151f5706c7b361123be32cc353bdf4b7f78e6,8352d4ff0e33f246a22da8516812bf8ff3ddbdecb6a6435fbcf08e9edcf989ab,18f89f4807de5493e83cbc19a87df51268050c5fb3a12f286e64c3115073dea7,673621352
 5gnidd,0.5,1,10,9,851123,851123,9,0,0,31613,140144,4.433112959858287,5,0,0,10,1.0506716688269377,1.4400757602882683,5065.0,f43906e111a8342c102237fe21090b64cadcc6e94c77db0deee1497e87e86801,0815c91ed82fe7e1502a49fa1de050fea9d5b037d051a0c3fb900d3a0f7bfa08,3d05b7fe48d5a06ce5076eb60084349adc777872a54ddd566f7461f2f0c3579e,1403944623
 5gnidd,0.5,2,10,9,851123,851123,9,2,2,20087,255463,12.717827450589933,6,2,1,10,1.4006658705096433,1.9640881124634801,3363.5,fe8b4fc6f0486cf4fadf97ea0e096e8c7439fadb1f4e747336313b3bfd52d023,fdcf388e31658ae11a6068e9dc2c6f27ef1567ecce60855efe6d8e3dc75cebf6,fc758d060dc51dec113b118e07cda6a012b5bd825aa64fb515d595cd1684417f,633461056
diff --git a/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_summary.csv b/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_summary.csv
index a89681d..c3c14dc 100644
--- a/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_summary.csv
+++ b/artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_summary.csv
@@ -1,3 +1,4 @@
 dataset,alpha,n_seeds,cells_sj_lt_M_total,cells_total,missing_client_class_cells_total,client_size_ratio_mean,client_size_ratio_max,union_unseen_mean,max_unseen_on_client,union_rare_mean,support_cv_mean,support_max_min_ratio_max
+5gnidd,0.25,3,16,27,30,17.600940070872678,27.82808487633464,5.333333333333333,3,6.666666666666667,1.3021194271854393,185504.0
 5gnidd,0.5,3,4,27,4,9.594308791178781,12.717827450589933,1.3333333333333333,1,5.666666666666667,1.2251708481787265,88943.0
 5gnidd,0.75,3,4,27,5,6.308651536045827,11.355971110240189,1.3333333333333333,1,6.0,0.9162099053779219,7642.5
diff --git a/artifacts/analysis/cross_dataset__beta_curve.csv b/artifacts/analysis/cross_dataset__beta_curve.csv
new file mode 100644
index 0000000..c483a9c
--- /dev/null
+++ b/artifacts/analysis/cross_dataset__beta_curve.csv
@@ -0,0 +1,31 @@
+dataset,dataset_name,alpha,beta,pooled_val_mean,pooled_val_std_sample,selected,cells_sj_lt_M_total,missing_client_class_cells_total,support_cv_mean,mean_displacement_beta1
+5gnidd,5G-NIDD,0.25,0.0,0.7614534210908004,0.021902537932118035,True,16,30,1.3021194271854393,2.91943348262683
+5gnidd,5G-NIDD,0.25,0.25,0.7492858468825278,0.017106975874172658,False,16,30,1.3021194271854393,2.91943348262683
+5gnidd,5G-NIDD,0.25,0.5,0.7257145491666086,0.01101731431676257,False,16,30,1.3021194271854393,2.91943348262683
+5gnidd,5G-NIDD,0.25,0.75,0.7222353067403979,0.007966771094060871,False,16,30,1.3021194271854393,2.91943348262683
+5gnidd,5G-NIDD,0.25,1.0,0.7376364240173013,0.002755842556750987,False,16,30,1.3021194271854393,2.91943348262683
+5gnidd,5G-NIDD,0.5,0.0,0.6872301309573783,0.052725844344546816,False,4,4,1.2251708481787265,2.3399083587182736
+5gnidd,5G-NIDD,0.5,0.25,0.6450777370820986,0.06474313739822393,False,4,4,1.2251708481787265,2.3399083587182736
+5gnidd,5G-NIDD,0.5,0.5,0.6746687817772702,0.10225286523806497,False,4,4,1.2251708481787265,2.3399083587182736
+5gnidd,5G-NIDD,0.5,0.75,0.6883680316141424,0.12603192659396695,False,4,4,1.2251708481787265,2.3399083587182736
+5gnidd,5G-NIDD,0.5,1.0,0.6923695590578484,0.13914040832229815,True,4,4,1.2251708481787265,2.3399083587182736
+5gnidd,5G-NIDD,0.75,0.0,0.7780936320958092,0.05096339060419691,False,4,5,0.9162099053779219,1.3846165631331337
+5gnidd,5G-NIDD,0.75,0.25,0.7904830018820702,0.05510032325554253,False,4,5,0.9162099053779219,1.3846165631331337
+5gnidd,5G-NIDD,0.75,0.5,0.8090814343293601,0.05873543815277214,True,4,5,0.9162099053779219,1.3846165631331337
+5gnidd,5G-NIDD,0.75,0.75,0.7915299789128217,0.06497400095064636,False,4,5,0.9162099053779219,1.3846165631331337
+5gnidd,5G-NIDD,0.75,1.0,0.8043064619946296,0.05480323650098284,False,4,5,0.9162099053779219,1.3846165631331337
+xiiotid,X-IIoTID,0.25,0.0,0.5917038146634539,0.08952883653922933,True,19,38,1.4423832412721973,3.4221253316893105
+xiiotid,X-IIoTID,0.25,0.25,0.5886906256417319,0.06643525635398827,False,19,38,1.4423832412721973,3.4221253316893105
+xiiotid,X-IIoTID,0.25,0.5,0.5858514801619258,0.044857849968223555,False,19,38,1.4423832412721973,3.4221253316893105
+xiiotid,X-IIoTID,0.25,0.75,0.5794633987349401,0.0649060573642385,False,19,38,1.4423832412721973,3.4221253316893105
+xiiotid,X-IIoTID,0.25,1.0,0.5320987006423418,0.045718338534042856,False,19,38,1.4423832412721973,3.4221253316893105
+xiiotid,X-IIoTID,0.5,0.0,0.5443606875936857,0.09144660841267144,False,7,9,1.1833344484214374,2.0985368999756338
+xiiotid,X-IIoTID,0.5,0.25,0.5554339572275921,0.09006816161098347,False,7,9,1.1833344484214374,2.0985368999756338
+xiiotid,X-IIoTID,0.5,0.5,0.5673218494926892,0.08853898624879539,False,7,9,1.1833344484214374,2.0985368999756338
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+xiiotid,X-IIoTID,0.75,0.0,0.471705692507431,0.055329314644425844,False,3,4,0.8806570470947873,1.3051104878964057
+xiiotid,X-IIoTID,0.75,0.25,0.47436809609801456,0.04605501919031881,False,3,4,0.8806570470947873,1.3051104878964057
+xiiotid,X-IIoTID,0.75,0.5,0.47674948263663786,0.04662425884469754,True,3,4,0.8806570470947873,1.3051104878964057
+xiiotid,X-IIoTID,0.75,0.75,0.47254095002934254,0.04602831582869046,False,3,4,0.8806570470947873,1.3051104878964057
+xiiotid,X-IIoTID,0.75,1.0,0.46860522897329,0.044741855341153436,False,3,4,0.8806570470947873,1.3051104878964057
diff --git a/artifacts/analysis/cross_dataset__matched_alpha_summary.csv b/artifacts/analysis/cross_dataset__matched_alpha_summary.csv
new file mode 100644
index 0000000..92256a8
--- /dev/null
+++ b/artifacts/analysis/cross_dataset__matched_alpha_summary.csv
@@ -0,0 +1,7 @@
+dataset,dataset_name,alpha,selected_beta,tie_break_used,test_used_for_selection,pooled_val_mean_min,pooled_val_mean_max,pooled_val_mean_spread,pooled_std_min,pooled_std_max,cells_sj_lt_M_total,cells_total,missing_client_class_cells_total,client_size_ratio_mean,support_cv_mean,union_unseen_mean,mean_displacement_beta1
+5gnidd,5G-NIDD,0.25,0.0,False,False,0.7222353067403979,0.7614534210908004,0.039218114350402455,0.002755842556750987,0.021902537932118035,16,27,30,17.600940070872678,1.3021194271854393,5.333333333333333,2.91943348262683
+5gnidd,5G-NIDD,0.5,1.0,False,False,0.6450777370820986,0.6923695590578484,0.04729182197574977,0.052725844344546816,0.13914040832229815,4,27,4,9.594308791178781,1.2251708481787265,1.3333333333333333,2.3399083587182736
+5gnidd,5G-NIDD,0.75,0.5,False,False,0.7780936320958092,0.8090814343293601,0.03098780223355091,0.05096339060419691,0.06497400095064636,4,27,5,6.308651536045827,0.9162099053779219,1.3333333333333333,1.3846165631331337
+xiiotid,X-IIoTID,0.25,0.0,False,False,0.5320987006423418,0.5917038146634539,0.05960511402111213,0.044857849968223555,0.08952883653922933,19,27,38,14.745270966890343,1.4423832412721973,5.666666666666667,3.4221253316893105
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diff --git a/artifacts/analysis/cross_dataset__matched_alpha_summary.json b/artifacts/analysis/cross_dataset__matched_alpha_summary.json
new file mode 100644
index 0000000..29521e4
--- /dev/null
+++ b/artifacts/analysis/cross_dataset__matched_alpha_summary.json
@@ -0,0 +1,516 @@
+{
+  "beta_curve": [
+    {
+      "alpha": 0.25,
+      "beta": 0.0,
+      "cells_sj_lt_M_total": 16,
+      "dataset": "5gnidd",
+      "dataset_name": "5G-NIDD",
+      "mean_displacement_beta1": 2.91943348262683,
+      "missing_client_class_cells_total": 30,
+      "pooled_val_mean": 0.7614534210908004,
+      "pooled_val_std_sample": 0.021902537932118035,
+      "selected": "True",
+      "support_cv_mean": 1.3021194271854393
+    },
+    {
+      "alpha": 0.25,
+      "beta": 0.25,
+      "cells_sj_lt_M_total": 16,
+      "dataset": "5gnidd",
+      "dataset_name": "5G-NIDD",
+      "mean_displacement_beta1": 2.91943348262683,
+      "missing_client_class_cells_total": 30,
+      "pooled_val_mean": 0.7492858468825278,
+      "pooled_val_std_sample": 0.017106975874172658,
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+}
diff --git a/docs/handoff/SESSION_HANDOFF.md b/docs/handoff/SESSION_HANDOFF.md
index 2c970c5..729e922 100644
--- a/docs/handoff/SESSION_HANDOFF.md
+++ b/docs/handoff/SESSION_HANDOFF.md
@@ -3,26 +3,30 @@
 This is the canonical continuation point for the next agent session. It is written to be
 readable without prior chat history, terminal scrollback, or git history.
 
-Last updated: 2026-09-29 (Session 10). Session 10 type: **second 5G-NIDD beta-validation
-condition**. Sessions 6–8 completed the X-IIoTID three-alpha study (`alpha=0.25/0.50/0.75`,
-seeds `{0,1,2}`); Session 9 ran 5G-NIDD `alpha=0.50` for seeds `{0,1,2}`. Session 10 ran **only**
-5G-NIDD `alpha=0.75` for seeds `{0,1,2}` across the five frozen beta candidates plus
-`original_protean`, using the same pooled-across-seed validation-only selection rule.
-**5G-NIDD alpha=0.25 was NOT run.** No commit or push was made.
+Last updated: 2026-09-30 (Session 11). Session 11 type: **final 5G-NIDD beta-validation condition**
+(`alpha=0.25`), completing the planned experiment grid. Sessions 6–8 completed the X-IIoTID
+three-alpha study (`alpha=0.25/0.50/0.75`, seeds `{0,1,2}`); Session 9 ran 5G-NIDD `alpha=0.50`;
+Session 10 ran 5G-NIDD `alpha=0.75`; Session 11 ran **only** 5G-NIDD `alpha=0.25` for seeds
+`{0,1,2}` across the five frozen beta candidates plus `original_protean`, using the same
+pooled-across-seed validation-only selection rule. **No condition was run after alpha=0.25.** No
+commit or push was made.
 
-> **Audit status (Session 10).** Independent audit verdict: **PASS**
-> (`docs/research/SESSION10_AUDIT.md`). `beta_star(5gnidd, alpha=0.75) = 0.50` confirmed from
+> **Audit status (Session 11).** Independent audit verdict: **PASS**
+> (`docs/research/SESSION11_AUDIT.md`). `beta_star(5gnidd, alpha=0.25) = 0.00` confirmed from
 > validation only; run inventory 18/18; pairing hash-identical and reproduced from raw data;
 > rare/unseen 0 mismatches over 1,620 cells; leakage audit PASS; `beta=0` class **B**; source/data
-> integrity PASS; pytest 75 passed. **Session 10 is safe to checkpoint.**
+> integrity PASS; pytest 75 passed. **Session 11 is safe to checkpoint.**
 
-> **Headline (Session 10).** PRIMARY pooled-validation selected beta for 5G-NIDD `alpha=0.75` =
-> **0.50** (validation only; per-seed diagnostics 0.50 / 1.00 / 1.00). The pooled validation curve
-> is **non-monotone** (0.778 → 0.790 → 0.809 → 0.792 → 0.804) and the total between-beta spread
-> (≈ 0.031) is smaller than the between-seed std (0.051–0.065), so the selection is statistically
-> weak. `beta=0` is class **B** for all three seeds. At alpha=0.75 the rare-class union is
-> **identical across seeds** and realized support imbalance is lower than at alpha=0.50, yet the
-> number of `|S_j|<M` cells is unchanged (4/27) and missing cells are slightly higher (5 vs 4).
+> **Headline (Session 11).** PRIMARY pooled-validation selected beta for 5G-NIDD `alpha=0.25` =
+> **0.00** (validation only; per-seed diagnostics 0.25 / 0.00 / 0.00). The pooled validation curve
+> declines from 0.761 (beta=0) to 0.722 (beta=0.75) and rises slightly to 0.738 (beta=1.0), with
+> the between-beta spread (0.039) exceeding the across-seed std (0.003–0.022). This is the first
+> condition where the selected beta is 0, i.e. the equal-`S_j` mean; the selected mode is therefore
+> numerically the baseline and shows no support-weighting benefit. `beta=0` is class **B** for all
+> three seeds. Realized heterogeneity is the highest of the three 5G-NIDD conditions
+> (16/27 `|S_j|<M` cells, 30 missing cells, client ratio mean 17.60, mean CV 1.302), and the
+> rare-class union differs across seeds (6/6/8), so this condition's test rare support is not
+> constant.
 
 ---
 
@@ -46,8 +50,8 @@ bitwise identical to the baseline (see §7).
 ## 2. Authoritative source and immutability
 
 - `planningawal/PROTEAN_Revisi_Lurus.md` — authoritative research specification.
-- `planningawal/` is immutable. Re-verified unchanged this session: `git status --short
-  planningawal/` and `git diff -- planningawal/` are both empty.
+- `planningawal/` is immutable. Re-verified unchanged this session: `git status --porcelain
+  planningawal/` empty.
 - Raw datasets re-verified unchanged (SHA-256):
   `~/datasets/5G-NIDD/5G-NIDD.csv`
   `fa36f80859585f474504ca69eb951a079b35145537976c86b00aae3aab46ee59`;
@@ -55,40 +59,42 @@ bitwise identical to the baseline (see §7).
   `7b9290057ee42e784da3c0d84b781815502c9205c74175c96374e71a5ffd98a0`.
 - Frozen baseline (`original_protean`) source unchanged; no `equal_available` mode added; beta
   candidate set unchanged (`{0, .25, .5, .75, 1}`). No tracked source/test/config file differs
-  from HEAD. The only new tracked-class file candidates are the new docs/artifacts listed in §16.
+  from HEAD. Only new docs/analysis artifacts are untracked.
 
-## 3. Session 10 objective and outcome
+## 3. Session 11 objective and outcome
 
-Objective: run exactly **one** new condition — 5G-NIDD `alpha=0.75`, seeds `{0,1,2}`,
-`original_protean` + five betas — after a Stage-A verification gate. Do not run alpha=0.25, do not
-launch the grid, do not change methodology.
+Objective: run exactly the **final** condition — 5G-NIDD `alpha=0.25`, seeds `{0,1,2}`,
+`original_protean` + five betas — after a Stage-A verification gate; then build the 5G-NIDD
+three-alpha comparison and the cross-dataset comparison. Do not run anything after it, do not
+change methodology.
 
-Stage A result: raw hash valid; all three 5G-NIDD `alpha=0.75` manifests reproduce exactly from raw
-data (support match, partition-hash match); label semantics and rare/unseen logic valid; pairing
-framework valid. Gate = **GO**.
+Stage A result: raw hash valid; all three 5G-NIDD `alpha=0.25` manifests reproduce exactly from raw
+data (support match, partition-hash match, split-hash match); label semantics and rare/unseen logic
+valid; pairing framework valid. Gate = **GO**.
 
-Outcome: 18/18 runs rc=0. **PRIMARY pooled-validation selected beta = 0.50** (validation only);
-`test_used_for_selection = false` for all 15 runs. Pooled means: 0.00 → 0.778094, 0.25 → 0.790483,
-0.50 → 0.809081, 0.75 → 0.791530, 1.00 → 0.804306. Reports:
-`docs/research/5GNIDD_ALPHA075_BETA_VALIDATION.md`, audit `docs/research/SESSION10_AUDIT.md`.
+Outcome: 18/18 runs rc=0. **PRIMARY pooled-validation selected beta = 0.00** (validation only);
+`test_used_for_selection = false` for all 15 runs. Pooled means: 0.00 → 0.761453, 0.25 → 0.749286,
+0.50 → 0.725715, 0.75 → 0.722235, 1.00 → 0.737636. Reports:
+`docs/research/5GNIDD_ALPHA025_BETA_VALIDATION.md`, `docs/research/5GNIDD_CROSS_ALPHA_ANALYSIS.md`,
+`docs/research/CROSS_DATASET_BETA_ANALYSIS.md`, audit `docs/research/SESSION11_AUDIT.md`.
 
 ## 4. Condition and pairing
 
 | Field | Value |
 |---|---|
-| dataset / alpha / seeds | `5gnidd` / 0.75 / `{0,1,2}` |
+| dataset / alpha / seeds | `5gnidd` / 0.25 / `{0,1,2}` |
 | runs | 15 `support_weighted` + 3 `original_protean`, all new this session |
 | training | 10 clients, 10 rounds, 3 local epochs, batch 256, lr 1e-3, mu 0.1, lambda 1.0, Adam |
-| code revision | unchanged from HEAD `a7f2b0049e99fb66021b4660b82a48d5dbbef072`; only docs/analysis added |
+| code revision | only docs/analysis added; HEAD `bbd35085063194db58e4472e70b204d4be4a3607` |
 
 Manifests (reused, never regenerated; one content hash per seed across all six runs; each
 reproduced from the raw dataset with split/`N_ij`/partition hash verified):
 
 | seed | manifest content hash | partition hash | split hash | rng seed | round-0 snapshot SHA-256 |
 |---|---|---|---|---|---|
-| 0 | `96cd9b90b71895da…` | `74a91845627dbe57…` | `18f89f48…` | 892370747 | `266a6e9976d5c138…` |
-| 1 | `007c23564a44919b…` | `fc04ba00f4942bf9…` | `3d05b7fe…` | 1817661572 | `acecab9a60852e45…` |
-| 2 | `3134bea2d47a7336…` | `4ee33d0a28326ae1…` | `fc758d06…` | 306220443 | `ef90c51aa9998ec8…` |
+| 0 | `ab6d8a8b63d478c4…` | `e628c17369f25e35…` | `18f89f4807de5493…` | 708356900 | `e2243ac4ed4391ff…` |
+| 1 | `74df102e4edb4509…` | `05aec12ceb4c94bd…` | `3d05b7fe48d5a06c…` | 902143161 | `26a162991b7cbde9…` |
+| 2 | `061c094d1913f942…` | `d9631ea6b2d3907e…` | `fc758d060dc51dec…` | 218373793 | `e287bff5ca71f8d2…` |
 
 Splits: train/validation/test = 851,123 / 121,589 / 243,177 for every seed (10 clients, 9 classes,
 `Benign`). `train_support_Nij.csv`, `characterization.csv`, `rare_unseen.csv` identical across each
@@ -98,61 +104,62 @@ hashes.
 ## 5. Validation results (USED FOR SELECTION) and pooled selection
 
 Primary metric: validation per-client-mean rare-class macro-F1. All 10 clients eligible in every
-seed. Full tables: `artifacts/analysis/5gnidd__alpha0.75__multiseed__validation_per_seed.csv`.
+seed. Full tables: `artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_per_seed.csv`.
 
 Per-seed validation per-client-mean rare-class macro-F1:
 
 | beta | seed 0 | seed 1 | seed 2 |
 |---|---|---|---|
-| 0.00 | 0.834681 | 0.763787 | 0.735812 |
-| 0.25 | 0.823388 | 0.821190 | 0.726871 |
-| 0.50 | **0.836792** | 0.848836 | 0.741617 |
-| 0.75 | 0.824667 | 0.833255 | 0.716668 |
-| 1.00 | 0.815774 | **0.852469** | **0.744677** |
+| 0.00 | 0.736360 | **0.771268** | **0.776732** |
+| 0.25 | **0.747299** | 0.767300 | 0.733259 |
+| 0.50 | 0.717450 | 0.738223 | 0.721471 |
+| 0.75 | 0.713262 | 0.728478 | 0.724966 |
+| 1.00 | 0.734455 | 0.739297 | 0.739157 |
 
 Pooled across seeds (`...__validation_pooled.csv`):
 
 | beta | pooled mean | std (sample) | min | max | selected |
 |---|---|---|---|---|---|
-| 0.00 | 0.778094 | 0.050963 | 0.735812 | 0.834681 | |
-| 0.25 | 0.790483 | 0.055100 | 0.726871 | 0.823388 | |
-| **0.50** | **0.809081** | 0.058735 | 0.741617 | 0.848836 | **yes** |
-| 0.75 | 0.791530 | 0.064974 | 0.716668 | 0.833255 | |
-| 1.00 | 0.804306 | 0.054803 | 0.744677 | 0.852469 | |
+| **0.00** | **0.761453** | 0.021903 | 0.736360 | 0.776732 | **yes** |
+| 0.25 | 0.749286 | 0.017107 | 0.733259 | 0.767300 | |
+| 0.50 | 0.725715 | 0.011017 | 0.717450 | 0.738223 | |
+| 0.75 | 0.722235 | 0.007967 | 0.713262 | 0.728478 | |
+| 1.00 | 0.737636 | 0.002756 | 0.734455 | 0.739297 | |
 
-- **PRIMARY selected beta (`beta_star_5gnidd_alpha075`) = 0.50**, max pooled validation
-  per-client-mean rare-class macro-F1; **no tie-break used**; validation-only.
-- **SECONDARY per-seed diagnostics only:** seed 0 → 0.50, seed 1 → 1.00, seed 2 → 1.00.
-- Between-beta spread ≈ 0.031; between-seed std 0.051–0.065 → statistically weak, descriptive.
+- **PRIMARY selected beta (`beta_star_5gnidd_alpha025`) = 0.00**, max pooled validation
+  per-client-mean rare-class macro-F1; **no tie-break used**; validation-only. Top-two gap ≈ 1.2e-2.
+- **SECONDARY per-seed diagnostics only:** seed 0 → 0.25, seed 1 → 0.00, seed 2 → 0.00.
+- Between-beta spread ≈ 0.039; between-seed std 0.003–0.022. At this condition the spread exceeds
+  the seed noise, but the sample is only 3 project-defined seeds.
 
 ## 6. Final test evaluation of the pooled-selected beta
 
-`beta_star = 0.50` was fixed from pooled validation before test was read.
+`beta_star = 0.00` was fixed from pooled validation before test was read.
 
 | metric (test) | seed 0 | seed 1 | seed 2 | mean ± std (sample) |
 |---|---|---|---|---|
-| rare-class macro-F1 | 0.904447 | 0.905721 | 0.880045 | 0.896738 ± 0.014470 |
-| rare-class recall | 0.958666 | 0.959723 | 0.960715 | 0.959701 ± 0.001025 |
-| macro-F1 | 0.857309 | 0.859939 | 0.842201 | 0.853150 ± 0.009572 |
-| accuracy | 0.749508 | 0.754381 | 0.752933 | 0.752274 ± 0.002503 |
-| weighted-F1 | 0.723885 | 0.730109 | 0.728408 | 0.727467 ± 0.003217 |
+| rare-class macro-F1 | 0.859893 | 0.813889 | 0.849925 | 0.841236 ± 0.024202 |
+| rare-class recall | 0.985234 | 0.972659 | 0.925756 | 0.961216 ± 0.031347 |
+| macro-F1 | 0.829680 | 0.802987 | 0.817254 | 0.816640 ± 0.013357 |
+| accuracy | 0.744844 | 0.737779 | 0.708052 | 0.730225 ± 0.019525 |
+| weighted-F1 | 0.717404 | 0.712302 | 0.683684 | 0.704463 ± 0.018175 |
 
 `original_protean` for the same seeds/condition:
 
 | metric (test) | seed 0 | seed 1 | seed 2 | mean ± std (sample) |
 |---|---|---|---|---|
-| rare-class macro-F1 | 0.905589 | 0.860758 | 0.873356 | 0.879901 ± 0.023121 |
-| rare-class recall | 0.961285 | 0.959036 | 0.963321 | 0.961214 ± 0.002144 |
-| macro-F1 | 0.857109 | 0.829867 | 0.837238 | 0.841405 ± 0.014091 |
-| accuracy | 0.747048 | 0.754072 | 0.751745 | 0.750955 ± 0.003578 |
-| weighted-F1 | 0.721059 | 0.729950 | 0.727133 | 0.726047 ± 0.004544 |
+| rare-class macro-F1 | 0.864903 | 0.814848 | 0.847072 | 0.842274 ± 0.025370 |
+| rare-class recall | 0.985444 | 0.972333 | 0.923890 | 0.960556 ± 0.032423 |
+| macro-F1 | 0.835043 | 0.808373 | 0.814800 | 0.819405 ± 0.013919 |
+| accuracy | 0.745280 | 0.741295 | 0.706329 | 0.730968 ± 0.021431 |
+| weighted-F1 | 0.718041 | 0.716327 | 0.681939 | 0.705435 ± 0.020367 |
 
 Descriptive difference for test rare-class macro-F1 (`beta_star` − `original_protean`) is
-−0.001141 / +0.044963 / +0.006689 (mean +0.016837). Test is descriptive only; no superiority or
-generalisation claimed. The global rare evaluation support is **28,000 for every seed** (rare-class
-union identical across seeds at alpha=0.75), so cross-seed test levels are directly comparable at
-this condition. Test weighted-F1 (`≈0.727`) again sits **below** accuracy (`≈0.752`), as at
-alpha=0.50.
+−0.005010 / −0.000959 / +0.002853 (mean −0.001039). Because beta_star = 0, this difference is just
+floating-point divergence (see §7). The global rare evaluation support differs by seed
+(**141,677 / 129,824 / 147,630**), so cross-seed test levels are **not** directly comparable at
+this condition. Test weighted-F1 (`≈0.704`) again sits **below** accuracy (`≈0.730`), as at
+alpha=0.50/0.75.
 
 ## 7. `beta = 0` equivalence result (all three seeds)
 
@@ -160,219 +167,243 @@ For seeds 0, 1, 2, `support_weighted beta=0` vs frozen `original_protean`:
 
 - Same manifest/split/hashes, round-0 snapshot byte-identical, support/char/rare_unseen
   identical: **yes** for all three.
-- Independent aggregation (`ΣC/n` vs `(1/n)ΣC`): 4.4e-16 / 4.4e-16 / 4.4e-16.
-- History rare-macro-F1 max diff (rounds ≥ 1): 3.22e-2 / 5.04e-2 / 2.72e-2; test metric max diff
-  5.22e-3 / 5.32e-3 / 2.74e-4.
+- Independent aggregation (`ΣC/n` vs `(1/n)ΣC`): 4.4e-16 / 4.4e-16 / 6.7e-16.
+- History rare-macro-F1 max diff (rounds ≥ 1): 2.17e-2 / 6.85e-2 / 2.74e-2; test metric max diff
+  5.36e-3 / 5.39e-3 / 2.85e-3.
 - Classification: **B** in all seeds — semantic equivalence + floating-point divergence; no
   semantic discrepancy. Machine-readable:
-  `artifacts/analysis/5gnidd__alpha0.75__multiseed__beta0_equivalence.csv`.
+  `artifacts/analysis/5gnidd__alpha0.25__multiseed__beta0_equivalence.csv`.
 
 Conditional on the shared `S_j` reproduction assumption; not proof `beta=0` reproduces original
-PROTEAN.
+PROTEAN. Since the selected beta is 0, the selected-run test metrics differ from original only by
+this divergence.
 
-## 8. Partition characterization (realized) and comparison with alpha=0.50
+## 8. Partition characterization (realized) and comparison with alpha=0.50/0.75
 
-5G-NIDD `alpha=0.75` (training split), `M = 10`:
+5G-NIDD `alpha=0.25` (training split), `M = 10`:
 
 | seed | `|S_j| < M` cells | missing client-class cells | client-size ratio | union rare | union unseen | max unseen/client |
 |---|---|---|---|---|---|---|---|
-| 0 | 2 / 9 | 3 | 3.70 | 6 | 2 | 1 |
-| 1 | 2 / 9 | 2 | 11.36 | 6 | 2 | 1 |
-| 2 | 0 / 9 | 0 | 3.87 | 6 | 0 | 0 |
-| **sum/mean** | **4 / 27** | **5** | mean **6.31** | 6/6/6 | 2/2/0 | 1 |
+| 0 | 6 / 9 | 10 | 9.93 | 6 | 6 | 3 |
+| 1 | 5 / 9 | 10 | 27.83 | 6 | 5 | 3 |
+| 2 | 5 / 9 | 10 | 15.05 | 8 | 5 | 2 |
+| **sum/mean** | **16 / 27** | **30** | mean **17.60** | 6/6/8 | 6/5/5 | 3 |
 
-All 10 clients have exactly two rare classes and are eligible in every seed. **The rare-class union
-is identical across all three seeds** (`{ICMPFlood, SYNFlood, SYNScan, SlowrateDoS, TCPConnectScan,
-UDPScan}`), so test rare support is constant (28,000). Mean class-support CV = **0.916**. Missing
-cells are single-client gaps: seed 0 (`ICMPFlood` c0/c3, `SYNFlood` c4), seed 1 (`ICMPFlood` c3,
-`SYNScan` c6). Full tables:
-`artifacts/analysis/5gnidd__alpha0.75__partition_heterogeneity_*` and
+Mean class-support CV = **1.302**; max per-class `max/min` = 185,504. All 10 clients have exactly
+two rare classes and are eligible. The rare-class union **differs across seeds** (6/6/8), so test
+rare support is not constant (141,677 / 129,824 / 147,630). This is the most heterogeneous of the
+three 5G-NIDD conditions. Full tables:
+`artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_*` and
 `...__partition_characterization.csv`.
 
-### Comparison with 5G-NIDD alpha=0.50 (descriptive)
+### 5G-NIDD three-alpha comparison
 
-| statistic | 5G-NIDD a0.50 | 5G-NIDD a0.75 |
-|---|---|---|
-| pooled-selected beta | **1.00** | **0.50** |
-| pooled validation mean range (spread) | 0.645–0.692 (0.047) | 0.778–0.809 (0.031) |
-| pooled validation std range | 0.053–0.139 | 0.051–0.065 |
-| `|S_j| < M` cells (sum/27) | 4/27 | 4/27 |
-| missing client-class cells | 4 | 5 |
-| client-size ratio mean | 9.59 | 6.31 |
-| mean class-support CV | 1.225 | 0.916 |
-| union rare per seed | 6/5/6 | 6/6/6 |
-| union unseen per seed | 2/0/2 | 2/2/0 |
-| test rare support per seed | 104,843 / 13,375 / 128,995 | 28,000 / 28,000 / 28,000 |
-| mean displacement `‖Cbar(1)−Cbar(0)‖` | 2.340 | 1.385 |
-| selected-beta client improve/degrade | 6/3, 3/5, 7/2 | 4/6, 6/3, 4/2 |
-| `beta=0` class | B/B/B | B/B/B |
+| statistic | a0.25 | a0.50 | a0.75 |
+|---|---|---|---|
+| pooled-selected beta | **0.00** | **1.00** | **0.50** |
+| `|S_j| < M` cells (sum/27) | **16/27** | 4/27 | 4/27 |
+| missing client-class cells | **30** | 4 | 5 |
+| client-size ratio mean | **17.60** | 9.59 | 6.31 |
+| mean class-support CV | **1.302** | 1.225 | 0.916 |
+| union rare per seed | 6/6/8 | 6/5/6 | 6/6/6 |
+| union unseen per seed | 6/5/5 | 2/0/2 | 2/2/0 |
+| test rare support per seed | 141,677 / 129,824 / 147,630 | 104,843 / 13,375 / 128,995 | 28,000 / 28,000 / 28,000 |
+| mean displacement `‖Cbar(1)−Cbar(0)‖` | **2.919** | 2.340 | 1.385 |
+| `beta=0` class | B/B/B | B/B/B | B/B/B |
 
-Higher alpha lowers **mean** support imbalance and mean displacement, but the number of
-`|S_j|<M` cells is unchanged and missing cells rise. No causal or monotone claim (two alpha levels).
-Machine-readable cross-alpha artifacts: `artifacts/analysis/5gnidd__cross_alpha__*`.
+Realized imbalance and mean displacement decrease as alpha rises; the selected beta is **not
+monotone** in alpha (0.00 → 1.00 → 0.50). No causal/monotone claim (three alphas, three seeds, one
+dataset).
 
 ## 9. Direct prototype-effect findings (fixed round-0 snapshots, no retraining)
 
-`||Cbar_j(1) − Cbar_j(0)||`, cross-seed mean (std), 5G-NIDD alpha=0.75:
+`||Cbar_j(1) − Cbar_j(0)||`, cross-seed mean (std), 5G-NIDD alpha=0.25:
 
 | class | mean disp | std |
 |---|---|---|
-| UDPScan | 2.445 | 0.484 |
-| SYNFlood | 1.897 | 0.171 |
-| SlowrateDoS | 1.565 | 0.654 |
-| SYNScan | 1.563 | 0.640 |
-| HTTPFlood | 1.366 | 0.544 |
-| TCPConnectScan | 1.226 | 0.476 |
-| UDPFlood | 0.903 | 0.103 |
-| Benign | 0.824 | 0.272 |
-| ICMPFlood | 0.673 | 0.331 |
+| SYNScan | 3.815 | 1.402 |
+| HTTPFlood | 3.760 | 1.539 |
+| TCPConnectScan | 3.258 | 2.574 |
+| SlowrateDoS | 3.179 | 1.157 |
+| SYNFlood | 3.176 | 1.007 |
+| UDPScan | 2.816 | 1.604 |
+| Benign | 2.648 | 0.519 |
+| UDPFlood | 2.408 | 0.578 |
+| ICMPFlood | 1.215 | 0.151 |
 
-Mean across classes **1.385** at beta=1.0 (monotone: 0.497 / 0.875 / 1.163 / 1.385 for beta
-0.25/0.50/0.75/1.00), smaller than at alpha=0.50 (2.340). Displacement is a direct-aggregation
-measure only, not a detection result. Outputs:
-`artifacts/analysis/5gnidd__alpha0.75__multiseed__prototype_effect_pooled.csv` and per-seed
+Mean across classes **2.919** at beta=1.0 (monotone: 1.295 / 2.055 / 2.559 / 2.919 for beta
+0.25/0.50/0.75/1.00), the largest of the three 5G-NIDD alphas (a0.50 = 2.340, a0.75 = 1.385).
+Displacement is a direct-aggregation measure only, not a detection result. Outputs:
+`artifacts/analysis/5gnidd__alpha0.25__multiseed__prototype_effect_pooled.csv` and per-seed
 `...__prototype_effect.csv` / `...__prototype_weights.csv`.
 
 ## 10. Client-level findings (validation, vs beta = 0)
 
 Detail: `...__client_validation_detail.csv`; summary: `...__client_validation_summary.csv`.
 
-At the selected `beta=0.50`: **4/6/0** (seed 0, mean Δ +0.0021, range −0.0434…+0.0744),
-**6/3/1** (seed 1, mean Δ +0.0850, range −0.0172…+0.2667), **4/2/4** (seed 2, mean Δ +0.0058).
-The response is seed-dependent and `N_ij` vs ΔF1 is non-monotonic. Client ids are per-seed
-realisations and are not pooled.
+At the selected `beta=0.00` the delta is trivially 0/0/10 in every seed. At a common
+`beta=0.75`: **3/4/3** (seed 0, mean Δ −0.023), **2/5/3** (seed 1, mean −0.043), **1/4/5** (seed 2,
+mean −0.052): at this low-alpha condition support weighting at beta=0.75 **degrades** the
+rare-class validation metric for most clients, consistent with the pooled selection of beta=0.
+`N_ij` vs ΔF1 is non-monotonic. Client ids are per-seed realisations and are not pooled.
 
 ## 11. Runtime / resources
 
-CPU only, no GPU, no swap, exit 0 on all 18 runs. Per-run wall-clock 61:55–66:37; CPU 738–745 %;
-peak RSS ~8.69 GiB (seed 0), ~11.78 GiB (seed 1), ~11.00 GiB (seed 2). New compute: 18 runs,
-**69,064 s ≈ 19.18 h** wall-clock, sequential (8 cores). Machine-readable:
-`artifacts/analysis/5gnidd__alpha0.75__multiseed__runtime.csv`.
+CPU only, no GPU, no swap, exit 0 on all 18 runs. Per-run wall-clock 62:00–64:48; CPU 739–743 %;
+peak RSS ~13.2 GiB (seed 0), ~11.9 GiB (seed 1), ~16.1 GiB (seed 2). New compute: 18 runs,
+**68,798 s ≈ 19.11 h** wall-clock, sequential (8 cores). Machine-readable:
+`artifacts/analysis/5gnidd__alpha0.25__multiseed__runtime.csv`.
 
-## 12. Methodological decisions / assumptions
+## 12. Cross-dataset comparison (descriptive; completed this session)
+
+Six-condition, validation-only pooled selections:
+
+| dataset | alpha=0.25 | alpha=0.50 | alpha=0.75 |
+|---|---|---|---|
+| 5G-NIDD | **0.00** (0.7615) | **1.00** (0.6924) | **0.50** (0.8091) |
+| X-IIoTID | **0.00** (0.5917) | **0.75** (0.5794) | **0.50** (0.4767) |
+
+- Matched-alpha selections coincide at alpha=0.25 (both 0.00) and alpha=0.75 (both 0.50) and
+  differ at alpha=0.50 (1.00 vs 0.75). The selected beta takes values `{0.00, 0.50, 1.00}` across
+  the six conditions — **not universal, not a function of alpha alone, not monotone**.
+- Realized heterogeneity is close but not identical at matched alpha (X-IIoTID has more missing
+  cells at alpha=0.25/0.50; 5G-NIDD has a higher client-size ratio). Dataset structural
+  differences and **rare-set composition differences are kept explicit**: 5G-NIDD rare classes are
+  low-volume flood/scan types; X-IIoTID rare classes are low-volume behavioural categories. A
+  "rare class" is not a comparable object across datasets.
+- Mean displacement at beta=1 falls with alpha on both datasets (5G-NIDD 2.919/2.340/1.385;
+  X-IIoTID 3.422/2.099/1.305).
+- No causality, no universal beta, no cross-dataset superiority, no monotone law. Machine-readable:
+  `artifacts/analysis/cross_dataset__matched_alpha_summary.csv` / `.json` and
+  `cross_dataset__beta_curve.csv`. Report: `docs/research/CROSS_DATASET_BETA_ANALYSIS.md`.
+
+## 13. Methodological decisions / assumptions
 
 1. **`S_j` participant/denominator rule** (`S_j = {i | N_ij > 0 and valid C_ij}`, equal weights in
-   the baseline) is a **REPRODUCTION ASSUMPTION**; material in **4/27** class-condition cells at
-   5G-NIDD alpha=0.75. Carry this caveat in all reporting.
+   the baseline) is a **REPRODUCTION ASSUMPTION**; material in **16/27** class-condition cells at
+   5G-NIDD alpha=0.25 (and 19/27 at X-IIoTID alpha=0.25). Carry this caveat in all reporting.
 2. `N_ij` is class-specific sample support, not prototype quality.
 3. Beta is one value for all classes/clients; candidates frozen at `{0,.25,.5,.75,1}`.
 4. **PRIMARY selection = pooled validation across clients and seeds**; per-seed selection is
    secondary stability diagnostics; test used only after the pooled beta is fixed.
 5. No new source scripts this session; analysis used the existing read-only
    `analyze_partition_heterogeneity.py`, `analyze_prototype_effect.py`, `analyze_multiseed_beta.py`,
-   `verify_beta0_equivalence.py`, `analyze_cross_alpha.py`. Ad-hoc Stage-A/audit helpers live only
-   under `/tmp/opencode/s10/` (outside the repo).
+   `verify_beta0_equivalence.py`, `analyze_cross_alpha.py`, plus the ad-hoc Session-11 helpers only
+   under `/tmp/opencode/s11/` (outside the repo).
 6. `lambda=1.0`, Adam, lr 1e-3, batch 256 remain PROJECT DECISIONS. No `equal_available` mode.
 
-## 13. Unresolved questions / blockers
+## 14. Unresolved questions / blockers
 
 1. `S_j` reproduction ambiguity — unresolved; no official PROTEAN code exists.
-2. Pooled beta selection remains statistically weak at all measured conditions: across-seed std is
-   comparable to the between-beta spread. No inferential test was performed.
+2. Pooled beta selection remains statistically weak at all six conditions; only three seeds.
 3. `beta = 0` is not bitwise identical to `original_protean`; documentation decision still open.
 4. Session-2 manifests still store `preprocessing_hash = null` / `config_hash = null`.
-5. 5G-NIDD now has alpha=0.50 (1.00) and alpha=0.75 (0.50); **alpha=0.25 remains unmeasured**, so
-   no 5G-NIDD alpha→beta trend can be stated.
-6. The selected beta differs across datasets/conditions (5G-NIDD a0.50 = 1.00, a0.75 = 0.50;
-   X-IIoTID a0.75 = 0.50) but no trend or causality is claimed.
+5. At both alpha=0.25 conditions the selected beta is 0, so those conditions cannot demonstrate a
+   support-weighting benefit.
+6. No inferential trend test; selected beta differs across conditions but no monotone/causal claim.
 
-## 14. Git status
+## 15. Git status
 
-No commit or push was made. `HEAD = a7f2b0049e99fb66021b4660b82a48d5dbbef072`, branch `main`,
-in sync with `origin/main`. `git status --short` shows only untracked docs/analysis artifacts (no
-tracked modification); `results/` is gitignored. `planningawal/` and both raw datasets are
-unchanged. `equal_available` absent. No test-based selection. The 18 runs are the only
-`results/5gnidd__alpha0.75__*` directories.
+No commit or push was made. `HEAD = bbd35085063194db58e4472e70b204d4be4a3607`, branch `main`, in
+sync with `origin/main`. Only untracked docs/analysis artifacts exist (no tracked modification);
+`results/` is gitignored. `planningawal/` and both raw datasets are unchanged. `equal_available`
+absent. No test-based selection. The 18 runs are the only `results/5gnidd__alpha0.25__*`
+directories.
 
-## 15. Session 10 audit result
+## 16. Session 11 audit result
 
-- Verdict: **PASS** (`docs/research/SESSION10_AUDIT.md`).
+- Verdict: **PASS** (`docs/research/SESSION11_AUDIT.md`).
 - Run inventory 18/18, pairing hash-identical, manifests reproduced from raw data.
-- Validation recomputed exactly; **pooled `beta_star(5gnidd, alpha=0.75) = 0.50`** (validation
+- Validation recomputed exactly; **pooled `beta_star(5gnidd, alpha=0.25) = 0.00`** (validation
   only). Selected-beta test and `original_protean` test means/stds exact.
 - Leakage audit PASS; `test_used_for_selection=false` upheld.
 - Rare/unseen integrity PASS (0 mismatches / 1,620 cells). `beta=0` equivalence class **B**.
-- Direct-effect, client-level, cross-condition labels: PASS.
+- Direct-effect, client-level, cross-alpha, cross-dataset labels: PASS.
 - Source/data integrity PASS. pytest: **75 passed, 0 failed, 0 skipped**.
 
-## 16. Files created / modified this session
+## 17. Files created / modified this session
 
 Created:
 
-- `docs/research/5GNIDD_ALPHA075_BETA_VALIDATION.md`
-- `docs/research/SESSION10_AUDIT.md`
-- `artifacts/analysis/5gnidd__alpha0.75__*` — 18 prototype snapshots + 6 per-seed
-  effect/weights CSVs + `5gnidd__alpha0.75__multiseed__*` (validation per-seed/pooled,
+- `docs/research/5GNIDD_ALPHA025_BETA_VALIDATION.md`
+- `docs/research/5GNIDD_CROSS_ALPHA_ANALYSIS.md`
+- `docs/research/CROSS_DATASET_BETA_ANALYSIS.md`
+- `docs/research/SESSION11_AUDIT.md`
+- `artifacts/analysis/5gnidd__alpha0.25__*` — 18 prototype snapshots + 3 per-seed
+  effect/weights CSVs + `5gnidd__alpha0.25__multiseed__*` (validation per-seed/pooled,
   client detail/summary/deltas, test descriptive, prototype effect pooled, beta0 equivalence,
-  runtime, selection summary, audit recomputation) + `5gnidd__alpha0.75__partition_heterogeneity_*`
-  + `5gnidd__alpha0.75__partition_characterization.csv` + `5gnidd__cross_alpha__*`
-- `results/5gnidd__alpha0.75__seed{0,1,2}__*` (18 run dirs, gitignored)
+  runtime, selection summary, audit recomputation) + `5gnidd__alpha0.25__partition_characterization.csv`
+- `artifacts/analysis/5gnidd__cross_alpha__*` (regenerated to include alpha=0.25)
+- `artifacts/analysis/cross_dataset__matched_alpha_summary.{csv,json}`,
+  `artifacts/analysis/cross_dataset__beta_curve.csv`
+- `results/5gnidd__alpha0.25__seed{0,1,2}__*` (18 run dirs, gitignored)
 
 Modified:
 
 - `docs/handoff/SESSION_HANDOFF.md` (this file)
+- `artifacts/analysis/5gnidd__cross_alpha__*` (extended from 2 to 3 alphas; previous 2-alpha
+  content was superseded, not silently lost — it is reproducible from the frozen manifests)
 
 No source or test code was changed.
 
-## 17. Exact recommended next phase
+## 18. Exact recommended next phase
 
-1. **Session 10 is audited and safe to checkpoint** (verdict PASS; see §15 and
-   `docs/research/SESSION10_AUDIT.md`). Before checkpointing, stage only the intended
-   docs/analysis artifacts; do not commit `results/` or the raw datasets.
-2. **5G-NIDD alpha=0.50 and alpha=0.75 are complete.** The final 5G-NIDD condition, **alpha=0.25**,
-   is **safe to run** — its manifest already exists and reproduces from raw data, the pipeline is
-   stable, and the same frozen protocol applies. Budget **≈19 h** (18 runs × ~64 min) and run
-   **one condition at a time**; do not launch the grid blindly.
-3. Follow the same pooled validation-only selection rule; report each selected beta as "best among
-   the tested candidates under pooled validation for that condition" — never a global optimum.
-4. After alpha=0.25, build the 5G-NIDD cross-alpha comparison (alpha=0.25/0.50/0.75) analogous to
-   `XIIOTID_CROSS_ALPHA_ANALYSIS.md`, and only then consider cross-dataset discussion.
-5. Do not infer a monotone alpha→beta relation; do not claim dataset causality.
-6. Update `EXPERIMENT_PROTOCOL.md` only if a real ambiguity appears; update this handoff.
-7. Do not commit or push unless asked.
+1. **Session 11 is audited and safe to checkpoint** (verdict PASS). Before checkpointing, stage
+   only the intended docs/analysis artifacts; do not commit `results/` or the raw datasets.
+2. **The planned experiment grid is COMPLETE** (two datasets × three alphas × three seeds × five
+   betas + baseline = 108 runs). Do **not** run any new condition.
+3. Remaining work is analysis/writing, not new training:
+   - optionally add an inferential comparison (e.g. paired sign/permutation test over seeds) to
+     formalise the weak selection effects — clearly labelled as post-hoc if added;
+   - freeze the final thesis tables/report from the six-condition artifacts;
+   - decide and document the `beta=0` vs `original_protean` reporting convention.
+4. Do not infer a monotone alpha→beta law; do not claim dataset causality or superiority.
+5. Update `EXPERIMENT_PROTOCOL.md` only if a real ambiguity appears; update this handoff.
+6. Do not commit or push unless asked.
 
-## 18. Important commands
+## 19. Important commands
 
 ```bash
 # Tests (75 expected)
 .venv/bin/python -m pytest
 
-# One full paired beta run (CPU, ~62-67 min, ~8.7-11.8 GiB for 5G-NIDD)
-.venv/bin/python scripts/run_baseline.py --dataset 5gnidd --alpha 0.75 --seed 1 \
+# One full paired beta run (CPU, ~62-65 min, ~12-17 GiB for 5G-NIDD)
+.venv/bin/python scripts/run_baseline.py --dataset 5gnidd --alpha 0.25 --seed 1 \
     --clients 10 --rounds 10 --local-epochs 3 \
     --aggregation-mode support_weighted --beta 1.0
 
 # Pooled multi-seed validation analysis (read-only, no retraining)
-.venv/bin/python scripts/analyze_multiseed_beta.py --dataset 5gnidd --alpha 0.75 --seeds 0 1 2
+.venv/bin/python scripts/analyze_multiseed_beta.py --dataset 5gnidd --alpha 0.25 --seeds 0 1 2
 
 # Direct prototype-effect analysis (no retraining)
 .venv/bin/python scripts/analyze_prototype_effect.py \
-    --snapshot artifacts/analysis/5gnidd__alpha0.75__seed0__support_weighted__beta0__prototype_snapshot.json \
+    --snapshot artifacts/analysis/5gnidd__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot.json \
     --class-names "Benign,HTTPFlood,ICMPFlood,SYNFlood,SYNScan,SlowrateDoS,TCPConnectScan,UDPFlood,UDPScan" \
     --output-dir artifacts/analysis
 
 # Realized partition characterization (cross-alpha)
-.venv/bin/python scripts/analyze_partition_heterogeneity.py --dataset 5gnidd --alphas 0.5 0.75
+.venv/bin/python scripts/analyze_partition_heterogeneity.py --dataset 5gnidd --alphas 0.25 0.5 0.75
 
 # beta=0 equivalence audit
-.venv/bin/python scripts/verify_beta0_equivalence.py --dataset 5gnidd --alpha 0.75 --seeds 0 1 2
+.venv/bin/python scripts/verify_beta0_equivalence.py --dataset 5gnidd --alpha 0.25 --seeds 0 1 2
 
 # Cross-alpha comparison table (5G-NIDD)
-.venv/bin/python scripts/analyze_cross_alpha.py --dataset 5gnidd --alphas 0.5 0.75 --tag 5gnidd__cross_alpha
+.venv/bin/python scripts/analyze_cross_alpha.py --dataset 5gnidd --alphas 0.25 0.5 0.75
 ```
 
-## 19. Recommended next-session prompt
+## 20. Recommended next-session prompt
 
 ```
-You are continuing the perdalam-protean research repository (Session 11).
+You are continuing the perdalam-protean research repository (Session 12).
 
 FIRST, read completely:
   1. docs/handoff/SESSION_HANDOFF.md
-  2. docs/research/5GNIDD_ALPHA075_BETA_VALIDATION.md
-  3. docs/research/SESSION10_AUDIT.md
-  4. docs/research/5GNIDD_ALPHA050_BETA_VALIDATION.md
-  5. docs/research/EXPERIMENT_PROTOCOL.md
+  2. docs/research/SESSION11_AUDIT.md
+  3. docs/research/5GNIDD_ALPHA025_BETA_VALIDATION.md
+  4. docs/research/5GNIDD_CROSS_ALPHA_ANALYSIS.md
+  5. docs/research/CROSS_DATASET_BETA_ANALYSIS.md
   6. docs/research/XIIOTID_CROSS_ALPHA_ANALYSIS.md
+  7. docs/research/EXPERIMENT_PROTOCOL.md
 
 Critical rules:
   - planningawal/ is immutable.
@@ -380,18 +411,15 @@ Critical rules:
   - The S_j participant rule is a REPRODUCTION ASSUMPTION.
   - Do NOT add an executable equal_available mode.
   - Beta selection uses validation only; PRIMARY is pooled across clients and seeds.
-  - Run one condition at a time (~19 h per 5G-NIDD condition).
+  - The planned 2-dataset x 3-alpha experiment grid is COMPLETE. Do NOT run new conditions.
 
-Context: Session 10 completed 5G-NIDD alpha=0.75 for seeds {0,1,2} (18 runs, ~19.18 h) and was
-independently audited (PASS; docs/research/SESSION10_AUDIT.md). Pooled validation selected
-beta=0.50 (per-seed diagnostics 0.50 / 1.00 / 1.00). beta=0 equivalence class B. Realized
-heterogeneity: 4/27 cells |S_j|<M, 5 missing cells, client ratio mean 6.31, mean displacement
-1.385, rare-class union identical across seeds. 5G-NIDD alpha=0.50 selected 1.00; X-IIoTID
-alpha=0.75 selected 0.50.
+Context: Session 11 ran the final condition 5G-NIDD alpha=0.25 (18 runs, ~19.11 h), audited PASS,
+and selected beta_star=0.00 (validation only; per-seed 0.25/0.00/0.00). The six-condition pooled
+selections are 5G-NIDD 0.25/0.50/0.75 = 0.00/1.00/0.50 and X-IIoTID = 0.00/0.75/0.50; no universal
+or monotone beta. beta=0 equivalence class B. pytest 75 passed.
 
-Task: run the final 5G-NIDD condition alpha=0.25 under the same frozen protocol (seeds {0,1,2},
-five betas + original_protean, frozen manifests, pooled validation-only selection). Verify the
-manifest reproduces, run the 18 runs sequentially with runtime/status files, produce a condition
-report + audit, and extend the 5G-NIDD cross-alpha comparison to alpha=0.25/0.50/0.75. Use
-.venv/bin/python. Do not commit or push unless asked.
+Task: no new training. Consolidate the final thesis-ready six-condition tables/report from the
+existing audited artifacts, optionally add a clearly post-hoc inferential comparison of the weak
+pooled selections, and keep all limitations (S_j assumption, three seeds, no global optimum)
+explicit. Use .venv/bin/python. Do not commit or push unless asked.
 ```
diff --git a/docs/research/5GNIDD_ALPHA025_BETA_VALIDATION.md b/docs/research/5GNIDD_ALPHA025_BETA_VALIDATION.md
new file mode 100644
index 0000000..6aa6f17
--- /dev/null
+++ b/docs/research/5GNIDD_ALPHA025_BETA_VALIDATION.md
@@ -0,0 +1,460 @@
+# 5G-NIDD Alpha-0.25 Beta Validation (Session 11)
+
+Status: **final 5G-NIDD beta-validation condition**. This report covers a single 5G-NIDD
+condition — `alpha = 0.25`, seeds `{0,1,2}`, the frozen `original_protean` baseline plus the five
+`support_weighted` beta candidates — using the same pooled-across-seed validation-only selection
+rule already applied to X-IIoTID (`alpha=0.25/0.50/0.75`) and 5G-NIDD `alpha=0.50/0.75`. It is
+**not** a sweep, not a hyper-parameter search, and not evidence of a global optimum. **No other
+5G-NIDD alpha was run**; `alpha=0.50` (Session 9) and `alpha=0.75` (Session 10) are reused only as
+audited references. No condition was run after this one.
+
+Companion documents:
+
+- `docs/research/EXPERIMENT_PROTOCOL.md` — frozen protocol and selection hierarchy.
+- `docs/research/5GNIDD_ALPHA050_BETA_VALIDATION.md` — audited 5G-NIDD alpha=0.50 reference.
+- `docs/research/5GNIDD_ALPHA075_BETA_VALIDATION.md` — audited 5G-NIDD alpha=0.75 reference.
+- `docs/research/SESSION9_AUDIT.md`, `docs/research/SESSION10_AUDIT.md` — prior audits.
+- `docs/research/XIIOTID_CROSS_ALPHA_ANALYSIS.md` — X-IIoTID three-condition reference.
+- `docs/research/5GNIDD_CROSS_ALPHA_ANALYSIS.md` — the resulting three-alpha 5G-NIDD comparison.
+- `docs/research/CROSS_DATASET_BETA_ANALYSIS.md` — two-dataset, three-alpha descriptive synthesis.
+- `docs/research/SESSION11_AUDIT.md` — independent audit of this condition.
+- `docs/handoff/SESSION_HANDOFF.md` — continuation point.
+
+---
+
+## A. Scope
+
+| Field | Value |
+|---|---|
+| dataset | `5gnidd` (5G-NIDD) |
+| alpha | 0.25 |
+| seeds | 0, 1, 2 |
+| aggregation | `original_protean` (per seed) + `support_weighted` for `beta ∈ {0, 0.25, 0.50, 0.75, 1.00}` |
+| runs | 18: 15 `support_weighted` + 3 `original_protean`, **all run new this session** |
+| compute | sequential CPU, one run at a time, 68,798 s ≈ **19.11 h** wall-clock |
+| selection | pooled validation-only across seeds `{0,1,2}` |
+| test | read only after the pooled beta was fixed |
+
+No 5G-NIDD `alpha=0.50` or `alpha=0.75` run was re-executed; the full grid was deliberately not
+launched. `equal_available` was not added. No training/aggregation/preprocessing source code was
+changed (HEAD `bbd35085063194db58e4472e70b204d4be4a3607`, unchanged).
+
+---
+
+## B. Dataset and manifests
+
+### B.1 Raw-data provenance (Stage A)
+
+- Path `~/datasets/5G-NIDD/5G-NIDD.csv`; SHA-256
+  `fa36f80859585f474504ca69eb951a079b35145537976c86b00aae3aab46ee59` — matches the audited
+  Session-9/10 value; **unmutated**.
+- Raw 1,215,890 rows; **1** exact duplicate dropped → 1,215,889; **0** label rows dropped.
+- **Label semantics (canonicalised):** label column `Attack Type`; **9 classes** — benign
+  `Benign` (index 0) plus **8 attack classes** (`HTTPFlood, ICMPFlood, SYNFlood, SYNScan,
+  SlowrateDoS, TCPConnectScan, UDPFlood, UDPScan`). Full-data counts unchanged from Session 9
+  (Benign 477,736; UDPFlood 457,340; HTTPFlood 140,812; SlowrateDoS 73,124; TCPConnectScan
+  20,052; SYNScan 20,043; UDPScan 15,906; SYNFlood 9,721; ICMPFlood 1,155).
+- **46 feature columns** (41 numeric median-imputed + train-standardized; 5 categorical one-hot
+  with an explicit `__MISSING__` category). Preprocessing fits on the train split only and is
+  identical to the previously audited pipeline (no source change).
+- Rare/unseen logic verified against this class list: attack classes only, `N_ij > 0`, two
+  smallest positive training supports per client, `N_ij = 0` is unseen (never rare), benign never
+  rare/unseen. All 10 clients are eligible in all three seeds (each has exactly two rare classes).
+
+### B.2 Manifest identity (frozen, never regenerated)
+
+Each `(alpha=0.25, seed)` manifest was independently reproduced from the raw dataset during Stage A
+(`prepare_dataset` → `reproduce_train_assignments`): exact `N_ij` match, partition-hash match and
+split-hash match. Train/validation/test sizes are 851,123 / 121,589 / 243,177 for every seed.
+
+| seed | manifest | manifest content hash | partition hash | split hash | rng seed |
+|---|---|---|---|---|---|
+| 0 | `artifacts/partitions/5gnidd__alpha0.25__seed0.json` | `ab6d8a8b63d478c4…` | `e628c17369f25e35…` | `18f89f4807de5493…` | 708356900 |
+| 1 | `artifacts/partitions/5gnidd__alpha0.25__seed1.json` | `74df102e4edb4509…` | `05aec12ceb4c94bd…` | `3d05b7fe48d5a06c…` | 902143161 |
+| 2 | `artifacts/partitions/5gnidd__alpha0.25__seed2.json` | `061c094d1913f942…` | `d9631ea6b2d3907e…` | `fc758d060dc51dec…` | 218373793 |
+
+`preprocessing_hash` / `config_hash` remain `null` in these Session-2 manifests (known limitation,
+carry-over).
+
+### B.3 Pairing (from content hashes, not filenames)
+
+Within each seed all six runs share one manifest content hash and a **byte-identical round-0
+snapshot**; `train_support_Nij.csv`, `characterization.csv` and `rare_unseen.csv` each have exactly
+one SHA-256 across the six runs; `manifest_reload_ok = true` and `smoke = false` everywhere.
+
+| seed | manifest content hash | round-0 snapshot SHA-256 (all 6 runs) |
+|---|---|---|
+| 0 | `ab6d8a8b63d478c4f6cfd88f96ccc7e16e1902f5e2c0ceac0f38ea26cfcda788` | `e2243ac4ed4391ff42ae358ab47ae4b98177227ac6e3ff0cdfd3a9147bf0d7c7` |
+| 1 | `74df102e4edb4509ba32b2625aa6a99f4bbd1dbbac0fc61d3bcccd50f21475ba` | `26a162991b7cbde947040c32c3d01b91841b6a58edc917038f813c8cbbd335b7` |
+| 2 | `061c094d1913f942267bdb5654d3c0d8cfef3fa592be6cd5a1845a5eb5cdc8f2` | `e287bff5ca71f8d2a677263ed17b67e909baaaada66cd9e1cb0c7f9e0c829b62` |
+
+18/18 runs present with `dataset=5gnidd, alpha=0.25`, 10 clients, 10 rounds, 3 local epochs,
+batch 256, lr 1e-3, mu 0.1, lambda 1.0; all exit status 0.
+
+---
+
+## C. Frozen protocol
+
+Identical to `EXPERIMENT_PROTOCOL.md` §14: 10 clients, 10 rounds, 3 local epochs, batch 256, Adam
+`lr=1e-3`, `mu=0.1`, `lambda=1.0`; unchanged architecture, preprocessing, split recipe, Dirichlet
+partition recipe (`per_class_dirichlet_multinomial`), loss and nearest-prototype inference. All 18
+runs used `scripts/run_baseline.py` at HEAD `bbd35085063194db58e4472e70b204d4be4a3607`.
+
+Selection rule (unchanged):
+
+- **PRIMARY:** pooled-across-seed validation per-client-mean rare-class macro-F1, validation only.
+- **SECONDARY (diagnostic):** per-seed validation selection.
+- **TEST:** read only after the pooled beta was fixed; `test_used_for_selection = false` for every
+  `support_weighted` run.
+
+---
+
+## D. Partition characterization (realized, before interpretation)
+
+All statistics are from the training-split `N_ij`; `M = 10` clients; `|S_j| < M` means fewer than
+10 clients contribute a prototype for a class.
+
+### D.1 Per-seed summary (alpha=0.25)
+
+| seed | `|S_j| < M` cells | missing client-class cells | client-size min/max (ratio) | union rare | union unseen | max unseen on a client |
+|---|---|---|---|---|---|---|---|
+| 0 | 6 / 9 | 10 | 23,943 / 237,693 (9.93) | 6 | 6 | 3 |
+| 1 | 5 / 9 | 10 | 7,399 / 205,900 (27.83) | 6 | 5 | 3 |
+| 2 | 5 / 9 | 10 | 19,817 / 298,192 (15.05) | 8 | 5 | 2 |
+| **total / mean** | **16 / 27** | **30** | ratio mean **17.60** | 6/6/8 | 6/5/5 | 3 |
+
+- `alpha=0.25` is the **most heterogeneous** of the three 5G-NIDD conditions: 16/27 class-condition
+  cells have `|S_j| < M`, 30 missing `(client,class)` cells, mean client-size ratio 17.60.
+- The **rare-class union is not identical across seeds**: seed 0 = `{ICMPFlood, HTTPFlood,
+  SYNFlood, TCPConnectScan, SlowrateDoS, UDPScan}`; seed 1 = `{ICMPFlood, HTTPFlood, SYNFlood,
+  SYNScan, TCPConnectScan, UDPFlood}`; seed 2 = all eight attack classes except none — seed 2 has
+  **8** union-rare classes. Consequently the global test rare support differs by seed
+  (141,677 / 129,824 / 147,630) and cross-seed test levels are **not** directly comparable.
+- All 10 clients have exactly two rare classes in every seed and are eligible.
+- Union unseen classes: seed 0 = 6 distinct (`HTTPFlood, ICMPFlood, SYNFlood, SYNScan,
+  SlowrateDoS, TCPConnectScan`), seed 1 = 5, seed 2 = 5; up to **3** unseen classes on a single
+  client (vs max 1 at alpha=0.50/0.75). This is a qualitative shift: at low alpha whole classes
+  vanish from a client.
+- Machine-readable: `artifacts/analysis/5gnidd__alpha0.25__partition_characterization.csv` and the
+  cross-alpha `5gnidd__cross_alpha__partition_heterogeneity_*` files.
+
+### D.2 Per-class support inequality
+
+Mean class-support CV across seeds = **1.302** (seed 0 1.440, seed 1 1.140, seed 2 1.327); the
+maximum per-class `max/min` ratio across seeds is 185,504 (Benign seed 0, driven by one client with
+a single sample). The rare/attack classes are strongly imbalanced at every seed. Complete per-class
+tables: `5gnidd__cross_alpha__partition_heterogeneity_per_class.csv`.
+
+### D.3 Comparison with the audited 5G-NIDD alpha=0.50 and alpha=0.75
+
+| statistic (training split) | 5G-NIDD a0.25 | 5G-NIDD a0.50 | 5G-NIDD a0.75 |
+|---|---|---|---|
+| `|S_j| < M` cells (sum / 27) | **16 / 27** | 4 / 27 | 4 / 27 |
+| missing client-class cells | **30** | 4 | 5 |
+| client-size ratio (seeds) | 9.93 / 27.83 / 15.05 | 11.63 / 4.43 / 12.72 | 3.70 / 11.36 / 3.87 |
+| client-size ratio mean | **17.60** | 9.59 | 6.31 |
+| mean class-support CV | **1.302** | 1.225 | 0.916 |
+| union rare per seed | 6 / 6 / 8 | 6 / 5 / 6 | 6 / 6 / 6 |
+| union unseen per seed | 6 / 5 / 5 | 2 / 0 / 2 | 2 / 2 / 0 |
+| max unseen on a client | **3** | 1 | 1 |
+
+Realized heterogeneity increases markedly as alpha falls. Note the client-size ratio is **not**
+uniformly ordered by seed (seed 0's ratio at alpha=0.50 is *higher* than at alpha=0.25), so these
+are realized statistics and are used for interpretation instead of alpha alone.
+
+---
+
+## E. Per-seed validation results
+
+`val rareMacroF1 (pc mean)` is the primary metric; all 10 clients eligible in every seed.
+Machine-readable: `artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_per_seed.csv`.
+
+### Seed 0
+
+| beta | val rareMacroF1 (pc mean) | val rareMacroF1 (global) | val rareRecall (global) | val macroF1 | val acc |
+|---|---|---|---|---|---|
+| **0.00** | **0.736360** | 0.863272 | 0.984162 | 0.831244 | 0.746359 |
+| 0.25 | **0.747299** | 0.883896 | 0.978293 | 0.847782 | 0.741490 |
+| 0.50 | 0.717450 | 0.822592 | 0.981845 | 0.806414 | 0.746383 |
+| 0.75 | 0.713262 | 0.803765 | 0.974314 | 0.804768 | 0.750808 |
+| 1.00 | 0.734455 | 0.804729 | 0.935751 | 0.820900 | 0.754986 |
+
+### Seed 1
+
+| beta | val rareMacroF1 (pc mean) | val rareMacroF1 (global) | val rareRecall (global) | val macroF1 | val acc |
+|---|---|---|---|---|---|
+| **0.00** | **0.771268** | 0.820509 | 0.974835 | 0.807348 | 0.737476 |
+| 0.25 | 0.767300 | 0.827350 | 0.970492 | 0.828781 | 0.751515 |
+| 0.50 | 0.738223 | 0.727485 | 0.844435 | 0.720389 | 0.666919 |
+| 0.75 | 0.728478 | 0.682389 | 0.759538 | 0.702449 | 0.639844 |
+| 1.00 | 0.739297 | 0.716268 | 0.799153 | 0.729077 | 0.671845 |
+
+### Seed 2
+
+| beta | val rareMacroF1 (pc mean) | val rareMacroF1 (global) | val rareRecall (global) | val macroF1 | val acc |
+|---|---|---|---|---|---|
+| **0.00** | **0.776732** | 0.842370 | 0.922437 | 0.810709 | 0.708074 |
+| 0.25 | 0.733259 | 0.778933 | 0.901942 | 0.754454 | 0.688138 |
+| 0.50 | 0.721471 | 0.744221 | 0.893070 | 0.723604 | 0.679272 |
+| 0.75 | 0.724966 | 0.774682 | 0.912452 | 0.750839 | 0.697703 |
+| 1.00 | 0.739157 | 0.825132 | 0.951026 | 0.795799 | 0.734014 |
+
+The per-seed curves are **non-monotone and seed-dependent**, but differ from the higher-alpha
+conditions: seed 0 peaks at 0.25 and again at 1.00 with a dip at 0.50–0.75; seed 1 is highest at
+0.00 and then falls; seed 2 is highest at 0.00. Increasing beta generally **reduces** the primary
+metric at this condition, with the notable exception of seed 0's small peak at 0.25. Seed 1 at
+beta ≥ 0.50 shows a large global-metric collapse (val accuracy 0.67–0.64), consistent with a
+rare-class-dominated partition where emphasizing high-support Benign/UDPFlood prototypes hurts
+nearest-prototype inference.
+
+---
+
+## F. Per-seed diagnostic beta choices (SECONDARY, stability only)
+
+| seed | selected beta | val rareMacroF1 (pc mean) | tie-break used | test_used_for_selection |
+|---|---|---|---|---|
+| 0 | 0.25 | 0.747299 | no | false |
+| 1 | 0.00 | 0.771268 | no | false |
+| 2 | 0.00 | 0.776732 | no | false |
+
+These per-seed choices are **diagnostic only**; they are not the condition-level selection rule.
+`val_selection.json` records `"selection_split": "validation"` and
+`"test_used_for_selection": false` for all 15 `support_weighted` runs.
+
+---
+
+## G. PRIMARY pooled-across-seed validation selection
+
+| beta | pooled mean | std (sample, ddof=1) | min | max | pooled val rareRecall (pc mean) | selected |
+|---|---|---|---|---|---|---|
+| **0.00** | **0.761453** | 0.021903 | 0.736360 | 0.776732 | 0.908577 | **yes** |
+| 0.25 | 0.749286 | 0.017107 | 0.733259 | 0.767300 | 0.907137 | |
+| 0.50 | 0.725715 | 0.011017 | 0.717450 | 0.738223 | 0.894947 | |
+| 0.75 | 0.722235 | 0.007967 | 0.713262 | 0.728478 | 0.879711 | |
+| 1.00 | 0.737636 | 0.002756 | 0.734455 | 0.739297 | 0.888991 | |
+
+- **PRIMARY selected beta (`beta_star_5gnidd_alpha025`) = 0.00.**
+- **Criterion:** maximum pooled validation per-client-mean rare-class macro-F1 (validation only);
+  tie-break order higher pooled rare recall → lower across-seed std → smaller beta.
+- **Tie-break used:** no. Top-two beta = 0.00 (0.761453) vs 0.25 (0.749286); gap ≈ **1.2e-2**.
+- **`test_used_for_selection = false`.** Test metrics were not inspected until the pooled beta was
+  fixed.
+- **Interpretation:** `beta = 0.00` is the *best among the tested candidates under pooled
+  validation across seeds `{0,1,2}` for 5G-NIDD alpha=0.25*. It is **not** a global optimum. The
+  pooled validation curve decreases from 0.761 at beta=0 to a minimum of 0.722 at beta=0.75, then
+  rises slightly to 0.738 at beta=1.00, so it is **non-monotone but overall declining**. The total
+  between-beta spread is ≈ **0.039**, while the across-seed sample std ranges 0.0028–0.0219. Unlike
+  alpha=0.50/0.75, at alpha=0.25 the across-seed std at beta=1.00 (0.0028) is *smaller* than the
+  between-beta spread, i.e. the seeds agree more closely at high beta; at beta=0.00 the std
+  (0.0219) is comparable to the spread. The pooled win of beta=0 is driven mainly by seed 2
+  (0.777 vs 0.733 at beta=0.25) and seed 1 (0.771 vs 0.767).
+- Selecting `beta=0.00` means the selected aggregation is the **equal mean over the shared `S_j`**,
+  i.e. mathematically the same mechanism as the `beta=0` control and numerically ~equal to the
+  frozen baseline (see §J). This makes the client-level "vs beta=0" delta trivially zero at the
+  selected beta.
+
+Machine-readable: `artifacts/analysis/5gnidd__alpha0.25__multiseed__validation_pooled.csv`,
+`...__selection_summary.json`.
+
+---
+
+## H. Final selected-beta test metrics (descriptive only)
+
+`beta_star = 0.00` was fixed from pooled validation; only then were test metrics read.
+
+| metric (test) | seed 0 | seed 1 | seed 2 | mean ± std (sample) |
+|---|---|---|---|---|
+| rare-class macro-F1 | 0.859893 | 0.813889 | 0.849925 | 0.841236 ± 0.024202 |
+| rare-class recall | 0.985234 | 0.972659 | 0.925756 | 0.961216 ± 0.031347 |
+| macro-F1 | 0.829680 | 0.802987 | 0.817254 | 0.816640 ± 0.013357 |
+| accuracy | 0.744844 | 0.737779 | 0.708052 | 0.730225 ± 0.019525 |
+| weighted-F1 | 0.717404 | 0.712302 | 0.683684 | 0.704463 ± 0.018175 |
+
+The global rare evaluation support differs by seed (**141,677 / 129,824 / 147,630**) because the
+training-derived union of rare classes differs at this alpha; cross-seed absolute test levels are
+therefore **not** directly comparable. Test columns:
+`artifacts/analysis/5gnidd__alpha0.25__multiseed__test_descriptive.csv`.
+
+---
+
+## I. `original_protean` comparison
+
+| metric (test) | seed 0 | seed 1 | seed 2 | mean ± std (sample) |
+|---|---|---|---|---|
+| rare-class macro-F1 | 0.864903 | 0.814848 | 0.847072 | 0.842274 ± 0.025370 |
+| rare-class recall | 0.985444 | 0.972333 | 0.923890 | 0.960556 ± 0.032423 |
+| macro-F1 | 0.835043 | 0.808373 | 0.814800 | 0.819405 ± 0.013919 |
+| accuracy | 0.745280 | 0.741295 | 0.706329 | 0.730968 ± 0.021431 |
+| weighted-F1 | 0.718041 | 0.716327 | 0.681939 | 0.705435 ± 0.020367 |
+
+Descriptive difference (`beta_star` − `original_protean`) for test rare-class macro-F1 is
+**−0.005010** (seed 0), **−0.000959** (seed 1), **+0.002853** (seed 2); mean **−0.001039**. As
+expected for a selected beta of 0, the selected-beta test metrics are numerically very close to the
+baseline, with small floating-point divergence (see §J). No superiority or generalisation is
+claimed. Descriptive dataset-level observation (consistent with alpha=0.50/0.75): on 5G-NIDD test
+weighted-F1 (`≈0.704`) sits **below** accuracy (`≈0.730`), the opposite of X-IIoTID.
+
+---
+
+## J. `beta = 0` equivalence vs `original_protean`
+
+| property | seed 0 | seed 1 | seed 2 |
+|---|---|---|---|
+| same manifest / split / hashes | yes | yes | yes |
+| round-0 snapshot byte-identical | yes (`e2243ac4…`) | yes (`26a16299…`) | yes (`e287bff5…`) |
+| support / characterization / rare_unseen identical | yes | yes | yes |
+| independent aggregation diff (`ΣC/n` vs `(1/n)ΣC`) | 4.4e-16 | 4.4e-16 | 6.7e-16 |
+| history rare-macro-F1 round-0 diff | 0.0 | 0.0 | 0.0 |
+| history rare-macro-F1 max diff (rounds ≥ 1) | 2.17e-2 | 6.85e-2 | 2.74e-2 |
+| test metric max abs diff | 5.36e-3 | 5.39e-3 | 2.85e-3 |
+| **classification** | **B** | **B** | **B** |
+
+Class **B**: semantic equivalence + floating-point numerical divergence; **no semantic
+discrepancy**. Round 0 is byte-identical; a ~1 ULP ordering difference enters round-1
+prototype-alignment training and the trajectories then diverge. Because the PRIMARY selection at
+this condition chose `beta=0.00`, the *selected* run is itself the `support_weighted beta=0` run,
+and the selected-beta test metrics differ from `original_protean` only by this floating-point
+divergence. Equivalence remains conditional on the shared `S_j` reproduction assumption and is
+**not** proof that `beta=0` reproduces original PROTEAN. Machine-readable:
+`artifacts/analysis/5gnidd__alpha0.25__multiseed__beta0_equivalence.csv`.
+
+---
+
+## K. Direct prototype-effect findings (fixed round-0 snapshots, no retraining)
+
+Computed from each seed's fixed `{C_ij, N_ij}` round-0 snapshot via the production aggregation.
+Cross-seed mean `||Cbar_j(beta) − Cbar_j(0)||` at `beta = 1.0` (sample std across seeds):
+
+| class | mean disp | std | mean rel disp |
+|---|---|---|---|
+| SYNScan | 3.815 | 1.402 | 0.544 |
+| HTTPFlood | 3.760 | 1.539 | 0.558 |
+| TCPConnectScan | 3.258 | 2.574 | 0.887 |
+| SlowrateDoS | 3.179 | 1.157 | 0.562 |
+| SYNFlood | 3.176 | 1.007 | 0.917 |
+| UDPScan | 2.816 | 1.604 | 0.371 |
+| Benign | 2.648 | 0.519 | 0.482 |
+| UDPFlood | 2.408 | 0.578 | 0.477 |
+| ICMPFlood | 1.215 | 0.151 | 0.347 |
+
+- Mean displacement across the nine classes is **2.919** at beta=1.0, monotone in beta
+  (0.25 → 1.295, 0.50 → 2.055, 0.75 → 2.559, 1.00 → 2.919).
+- Displacement is largest at this condition (2.919) among the three 5G-NIDD alphas and highest for
+  the imbalanced rare/scan classes; `ICMPFlood` (very low support) and `UDPFlood` (very high
+  support) move least.
+- Displacement is a **direct-aggregation measure only** and is **not** interpreted as improved or
+  degraded detection. The end-to-end effect is reported separately in §E/§H.
+
+Outputs: `artifacts/analysis/5gnidd__alpha0.25__seed{0,1,2}__support_weighted__beta0__prototype_snapshot__prototype_effect.csv`
+and `...__prototype_weights.csv`; cross-seed aggregate
+`artifacts/analysis/5gnidd__alpha0.25__multiseed__prototype_effect_pooled.csv`.
+
+---
+
+## L. Client-level effect (validation, relative to beta = 0)
+
+Detail: `...__client_validation_detail.csv`; summary: `...__client_validation_summary.csv`. Client
+ids are per-seed realisations and are **not** pooled across seeds. Tolerance 1e-9.
+
+**At the selected `beta = 0.00` the delta is trivially 0 for all clients in all seeds** (selected
+beta = reference beta). To describe the response, here is the full curve of mean Δ per seed:
+
+| beta | seed 0 (imp/deg/unch, mean Δ) | seed 1 | seed 2 |
+|---|---|---|---|
+| 0.00 | 0/0/10, 0.0000 | 0/0/10, 0.0000 | 0/0/10, 0.0000 |
+| 0.25 | 3/3/4, +0.0109 | 3/3/4, −0.0040 | 0/4/6, −0.0435 |
+| 0.50 | 3/4/3, −0.0189 | 2/4/4, −0.0330 | 1/3/6, −0.0553 |
+| 0.75 | 3/4/3, −0.0231 | 2/5/3, −0.0428 | 1/4/5, −0.0518 |
+| 1.00 | 3/4/3, −0.0019 | 3/4/3, −0.0320 | 4/3/3, −0.0376 |
+
+- At a common non-zero `beta = 0.75`, improve/degrade/unchanged = **3/4/3** (seed 0, mean
+  −0.023), **2/5/3** (seed 1, mean −0.043), **1/4/5** (seed 2, mean −0.052) — i.e. at low alpha
+  emphasizing support generally **degrades** the rare-class metric, the opposite of the higher
+  alpha conditions and consistent with the pooled selection of beta=0.
+- `N_ij` vs ΔF1 is **non-monotonic**: at beta=0.75 the worst seed-1 degradation (c5, −0.406) has
+  min positive attack `N_ij = 2`, but the best seed-0 gain (c5, +0.081) has min `N_ij = 1`; the
+  worst seed-2 degradation (c9, −0.268) has min `N_ij = 33`.
+- This analysis is descriptive and non-causal.
+
+---
+
+## M. Runtime and resources
+
+CPU only, no GPU, no swap, exit status 0 for every run (`/usr/bin/time -v`). Full table:
+`artifacts/analysis/5gnidd__alpha0.25__multiseed__runtime.csv`.
+
+| group | wall range | CPU % | peak RSS |
+|---|---|---|---|
+| seed 0 (6 runs) | 62:00 – 63:28 | 743 | 13.18 – 13.20 GiB |
+| seed 1 (6 runs) | 64:16 – 64:48 | 740–742 | 11.92 – 11.95 GiB |
+| seed 2 (6 runs) | 62:57 – 64:28 | 739–741 | 16.09 – 16.11 GiB |
+
+- New compute this session: **18 runs, 68,798 s ≈ 19.11 h** wall-clock, sequential on an 8-core
+  host.
+- Per-run wall time is homogeneous (62:00–64:48). Peak RSS is partition-dependent, not
+  beta-dependent: ~13.2 GiB (seed 0), ~11.9 GiB (seed 1), ~16.1 GiB (seed 2), all within the host
+  memory. 5G-NIDD uses more memory than X-IIoTID because the training split is ~1.5× larger.
+- No warnings, no client failures, 9/9 global prototypes in every round, no retries.
+
+---
+
+## N. Comparison with 5G-NIDD alpha=0.50 and alpha=0.75 (descriptive only)
+
+| statistic | 5G-NIDD a0.25 | 5G-NIDD a0.50 | 5G-NIDD a0.75 |
+|---|---|---|---|
+| pooled-selected beta | **0.00** | 1.00 | 0.50 |
+| pooled validation mean range (spread) | 0.722–0.761 (0.039) | 0.645–0.692 (0.047) | 0.778–0.809 (0.031) |
+| pooled validation std range | 0.003–0.022 | 0.053–0.139 | 0.051–0.065 |
+| `|S_j| < M` cells (sum / 27) | **16 / 27** | 4 / 27 | 4 / 27 |
+| missing client-class cells | **30** | 4 | 5 |
+| client-size ratio mean | **17.60** | 9.59 | 6.31 |
+| mean class-support CV | **1.302** | 1.225 | 0.916 |
+| union rare per seed | 6 / 6 / 8 | 6 / 5 / 6 | 6 / 6 / 6 |
+| union unseen per seed | 6 / 5 / 5 | 2 / 0 / 2 | 2 / 2 / 0 |
+| test rare support per seed | 141,677 / 129,824 / 147,630 | 104,843 / 13,375 / 128,995 | 28,000 / 28,000 / 28,000 |
+| mean displacement `‖Cbar(1)−Cbar(0)‖` | **2.919** | 2.340 | 1.385 |
+| selected-beta client improve/degrade | 0/0 (trivial at beta=0) | 6/3, 3/5, 7/2 | 4/6, 6/3, 4/2 |
+| `beta=0` equivalence class (per seed) | B / B / B | B / B / B | B / B / B |
+
+Descriptive observations (three alpha levels, one dataset, three project-defined seeds — **no
+monotone or causal claim**):
+
+- All three pooled validation curves are **non-monotone**, and the selected beta differs across
+  conditions (0.00 at alpha=0.25, 1.00 at alpha=0.50, 0.50 at alpha=0.75). The three selected
+  values are **not** monotone in alpha.
+- Realized support imbalance is largest at alpha=0.25 (CV 1.302, client ratio 17.60, 30 missing
+  cells, 16/27 `|S_j|<M` cells) and mean prototype displacement is also largest (2.919), tracking
+  the mechanical `N_ij^beta` sensitivity.
+- At alpha=0.25 the selection of `beta=0` coincides with the best pooled validation rarity, i.e.
+  the support-weighted mechanism does **not** help rare-class validation at this condition; this is
+  the opposite of alpha=0.50. Selection remains statistically weak (between-beta spread 0.039 vs
+  across-seed std up to 0.022).
+- Validation **levels** are not directly comparable across alpha (different rare-class sets and
+  per-client eval partitions); only within-condition contrasts are interpreted.
+
+Machine-readable: `artifacts/analysis/5gnidd__cross_alpha__cross_alpha_beta_table.csv`,
+`..._displacement.csv`, `..._client_summary.csv`, `..._summary.json` and
+`5gnidd__cross_alpha__partition_heterogeneity_*`.
+
+---
+
+## O. Limitations
+
+- **One new condition** (5G-NIDD alpha=0.25). This is the final 5G-NIDD condition, so the 5G-NIDD
+  three-alpha grid is complete; a cross-alpha comparison is now possible but remains descriptive.
+  No X-IIoTID/5G-NIDD causal or monotone claim.
+- **Three project-defined seeds** (`{0,1,2}`); the pooled selection at this condition has
+  between-beta spread larger than the across-seed std, but the result is still a weak descriptive
+  preference, not a strong effect. `beta_star = 0.00` is only "best among the five tested
+  candidates under pooled validation for this condition".
+- The `S_j` participant/denominator rule (`S_j = {i | N_ij > 0 and valid C_ij}`, equal weights in
+  the baseline) remains a **REPRODUCTION ASSUMPTION**. At 5G-NIDD alpha=0.25 it is material in
+  **16/27** class-condition cells, the largest of the three conditions; the `beta=0` comparison is
+  conditional on both modes sharing this rule and does **not** prove `beta=0` reproduces original
+  PROTEAN.
+- Train/validation/test adaptation (70/10/20 stratified) differs from the paper's literal 80/20;
+  the validation eval partition is a project decision.
+- `preprocessing_hash`/`config_hash` remain `null` in the 5G-NIDD manifests.
+- Selecting `beta=0` makes the selected mode arithmetically the equal-`S_j` mean, so this condition
+  yields no evidence that support weighting improves rare-class detection.
+- **No global beta optimum claim**; test metrics did not influence selection.
diff --git a/docs/research/5GNIDD_CROSS_ALPHA_ANALYSIS.md b/docs/research/5GNIDD_CROSS_ALPHA_ANALYSIS.md
new file mode 100644
index 0000000..d09395e
--- /dev/null
+++ b/docs/research/5GNIDD_CROSS_ALPHA_ANALYSIS.md
@@ -0,0 +1,262 @@
+# 5G-NIDD Cross-Alpha Analysis (alpha = 0.25 / 0.50 / 0.75)
+
+Status: **descriptive three-condition comparison** of the frozen beta protocol on 5G-NIDD, using
+the audited condition-level pooled results of Session 11 (`alpha=0.25`), Session 9 (`alpha=0.50`)
+and Session 10 (`alpha=0.75`). This document does **not** run anything and does not make a causal
+or monotonicity claim. Machine-readable counterpart:
+`artifacts/analysis/5gnidd__cross_alpha__cross_alpha_beta_table.csv`, `..._summary.json`,
+`..._displacement.csv`, `..._client_summary.csv`, and
+`artifacts/analysis/5gnidd__cross_alpha__partition_heterogeneity_*.csv`.
+
+Companion documents: `docs/research/5GNIDD_ALPHA025_BETA_VALIDATION.md`,
+`docs/research/5GNIDD_ALPHA050_BETA_VALIDATION.md`,
+`docs/research/5GNIDD_ALPHA075_BETA_VALIDATION.md`,
+`docs/research/EXPERIMENT_PROTOCOL.md`, `docs/research/XIIOTID_CROSS_ALPHA_ANALYSIS.md`,
+`docs/research/CROSS_DATASET_BETA_ANALYSIS.md`, `docs/handoff/SESSION_HANDOFF.md`.
+
+---
+
+## A. Experimental scope
+
+| Field | Value |
+|---|---|
+| dataset | 5G-NIDD (`5gnidd`) |
+| alpha | 0.25, 0.50, 0.75 |
+| seeds | 0, 1, 2 |
+| betas | 0.00, 0.25, 0.50, 0.75, 1.00 |
+| aggregation | `original_protean` + `support_weighted` |
+| selection | pooled validation-only per condition, seeds `{0,1,2}` |
+| test | read only after each condition's pooled beta is fixed |
+
+All three conditions share the frozen training protocol: 10 clients, 10 rounds, 3 local epochs,
+batch 256, Adam `lr=1e-3`, `mu=0.1`, `lambda=1.0`, unchanged architecture/preprocessing/split
+recipe/loss/inference. For each `(alpha, seed)` all six runs share one manifest and a
+byte-identical round-0 snapshot. 54 runs total (18 per condition).
+
+---
+
+## B. Realized heterogeneity
+
+`|S_j| < M` counts class-condition cells with fewer than 10 contributing clients, summed over
+the three seeds (out of 27). Missing cells count `(client, class)` pairs with `N_ij = 0`.
+
+| statistic | alpha=0.25 | alpha=0.50 | alpha=0.75 |
+|---|---|---|---|
+| `|S_j| < M` cells (sum over 3 seeds) | **16 / 27** | 4 / 27 | 4 / 27 |
+| missing client-class cells | **30** | 4 | 5 |
+| client-size ratio (seed 0/1/2) | 9.93 / 27.83 / 15.05 | 11.63 / 4.43 / 12.72 | 3.70 / 11.36 / 3.87 |
+| client-size ratio mean | **17.60** | 9.59 | 6.31 |
+| union rare classes per seed | 6 / 6 / 8 | 6 / 5 / 6 | 6 / 6 / 6 |
+| union unseen classes per seed | 6 / 5 / 5 | 2 / 0 / 2 | 2 / 2 / 0 |
+| max unseen classes on a client | **3** | 1 | 1 |
+| mean class-support CV | **1.302** | 1.225 | 0.916 |
+| max per-class max/min ratio (over seeds) | 185,504 | 88,943 | 7,642.5 |
+
+Realized heterogeneity increases as alpha falls, but **not uniformly per seed** (e.g. at
+alpha=0.50 seed 0 the client ratio 11.63 exceeds alpha=0.25 seed 0's 9.93). Interpretation uses
+these realized partitions, not alpha alone. The rarest attack class (`ICMPFlood`, 1,155 records
+full-data) is always rare; the rare-set union is seed-dependent only at alpha=0.25, where seed 2
+has 8 union-rare classes.
+
+---
+
+## C. Pooled validation curves (alpha × beta)
+
+Pooled validation per-client-mean rare-class macro-F1 (selection metric; validation only):
+
+| beta | alpha=0.25 mean (std) | alpha=0.50 mean (std) | alpha=0.75 mean (std) |
+|---|---|---|---|
+| **0.00** | **0.761453** (0.021903) | 0.687230 (0.052726) | 0.778094 (0.050963) |
+| 0.25 | 0.749286 (0.017107) | 0.645078 (0.064743) | 0.790483 (0.055100) |
+| 0.50 | 0.725715 (0.011017) | 0.674669 (0.102253) | **0.809081** (0.058735) |
+| 0.75 | 0.722235 (0.007967) | 0.688368 (0.126032) | 0.791530 (0.064974) |
+| 1.00 | 0.737636 (0.002756) | **0.692370** (0.139140) | 0.804306 (0.054803) |
+| **curve shape** | declines to 0.75, slight rise at 1.0 | rises to peak at 1.0 | peaks at 0.50, declines both sides |
+| **total between-beta spread** | 0.0392 | 0.0473 | 0.0308 |
+
+The across-seed sample std (0.003–0.139) is comparable to or larger than the between-beta spread at
+alpha=0.50 and alpha=0.75; at alpha=0.25 the between-beta spread (0.039) exceeds the across-seed
+std at every beta except beta=0.00, so the alpha=0.25 selection is relatively less seed-noise
+dominated — but it is still only three project-defined seeds and needs no causal reading.
+
+---
+
+## D. Selected beta by condition
+
+Condition-level **pooled** selections only (per-seed diagnostics are excluded):
+
+| condition | pooled-selected beta | pooled validation mean | tie-break used | per-seed diagnostic betas |
+|---|---|---|---|---|
+| alpha=0.25 | **0.00** | 0.761453 | no | 0.25 / 0.00 / 0.00 |
+| alpha=0.50 | **1.00** | 0.692370 | no | 1.00 / 0.00 / 1.00 |
+| alpha=0.75 | **0.50** | 0.809081 | no | 0.50 / 1.00 / 1.00 |
+
+The selected beta **changes with the non-IID condition but is not monotone** in alpha
+(0.00 → 1.00 → 0.50). At alpha=0.25 and alpha=0.75 the per-seed diagnostics partly disagree with
+the pooled choice, confirming seed sensitivity.
+
+---
+
+## E. Selected-beta test summaries (descriptive)
+
+Selected beta vs `original_protean`, mean ± sample std across seeds `{0,1,2}`.
+
+| condition | selected beta | test rare macro-F1 (selected) | test rare macro-F1 (original) | test macro-F1 (selected) | test macro-F1 (original) | test acc (selected) | test acc (original) |
+|---|---|---|---|---|---|---|---|
+| alpha=0.25 | 0.00 | 0.841236 ± 0.024202 | 0.842274 ± 0.025370 | 0.816640 ± 0.013357 | 0.819405 ± 0.013919 | 0.730225 ± 0.019525 | 0.730968 ± 0.021431 |
+| alpha=0.50 | 1.00 | 0.871984 ± 0.028501 | 0.880542 ± 0.037058 | 0.838596 ± 0.019627 | 0.842395 ± 0.020840 | 0.743257 ± 0.000667 | 0.743975 ± 0.008393 |
+| alpha=0.75 | 0.50 | 0.896738 ± 0.014470 | 0.879901 ± 0.023121 | 0.853150 ± 0.009572 | 0.841405 ± 0.014091 | 0.752274 ± 0.002503 | 0.750955 ± 0.003578 |
+
+**Do not compare the absolute test rare-class macro-F1 across conditions**: the training-derived
+union of rare classes (and hence the global rare evaluation support) differs by alpha and seed
+(alpha=0.25 support 141,677 / 129,824 / 147,630; alpha=0.50 104,843 / 13,375 / 128,995;
+alpha=0.75 28,000 / 28,000 / 28,000). Only the selected-vs-original difference *within* a condition
+is meaningful, and even that is dominated by between-seed variance. At alpha=0.25 and alpha=0.50
+the selected beta is numerically essentially the baseline (selected−original rare macro-F1 mean
+−0.0010 and −0.0086); at alpha=0.75 it is +0.0168. No superiority or generalisation is claimed.
+
+---
+
+## F. `original_protean` summaries
+
+`original_protean` test means (± sample std) across seeds:
+
+| condition | rare macro-F1 | rare recall | macro-F1 | accuracy | weighted-F1 |
+|---|---|---|---|---|---|
+| alpha=0.25 | 0.842274 ± 0.025370 | 0.960556 ± 0.032423 | 0.819405 ± 0.013919 | 0.730968 ± 0.021431 | 0.705435 ± 0.020367 |
+| alpha=0.50 | 0.880542 ± 0.037058 | 0.972913 ± 0.003843 | 0.842395 ± 0.020840 | 0.743975 ± 0.008393 | 0.718730 ± 0.008678 |
+| alpha=0.75 | 0.879901 ± 0.023121 | 0.961214 ± 0.002144 | 0.841405 ± 0.014091 | 0.750955 ± 0.003578 | 0.726047 ± 0.004544 |
+
+At every 5G-NIDD alpha, test weighted-F1 is **below** accuracy, i.e. the high-support
+`Benign`/`UDPFlood` classes are the harder ones for nearest-prototype inference — a dataset
+characteristic, not a beta effect.
+
+---
+
+## G. Direct prototype displacement (beta = 1 vs beta = 0)
+
+Cross-seed mean `||Cbar_j(1) − Cbar_j(0)||` on the fixed round-0 snapshots (no retraining):
+
+| class | alpha=0.25 | alpha=0.50 | alpha=0.75 |
+|---|---|---|---|
+| UDPScan | 2.816 | 3.461 | 2.445 |
+| SYNFlood | 3.176 | 2.262 | 1.897 |
+| SlowrateDoS | 3.179 | 2.763 | 1.565 |
+| SYNScan | 3.815 | 2.875 | 1.563 |
+| HTTPFlood | 3.760 | 3.120 | 1.366 |
+| TCPConnectScan | 3.258 | 2.131 | 1.226 |
+| UDPFlood | 2.408 | 1.598 | 0.903 |
+| Benign | 2.648 | 1.690 | 0.824 |
+| ICMPFlood | 1.215 | 1.159 | 0.673 |
+| **mean across classes** | **2.919** | **2.340** | **1.385** |
+
+Displacement by beta (cross-class mean), showing monotone growth in beta within each condition:
+
+| beta | alpha=0.25 | alpha=0.50 | alpha=0.75 |
+|---|---|---|---|
+| 0.25 | 1.295 | 0.953 | 0.497 |
+| 0.50 | 2.055 | 1.567 | 0.875 |
+| 0.75 | 2.559 | 2.003 | 1.163 |
+| 1.00 | 2.919 | 2.340 | 1.385 |
+
+Mean displacement tracks realized support imbalance (alpha=0.25 > 0.50 > 0.75), but the per-class
+rank order is seed-sensitive and differs across alpha (e.g. `UDPScan` is largest at alpha=0.50 but
+not at alpha=0.25/0.75). Displacement is a direct-aggregation measure only; it is **not**
+interpreted as improved or degraded detection.
+
+---
+
+## H. Client-level behaviour
+
+Improve/degrade/unchanged counts (validation, relative to `beta = 0`).
+
+At each condition's pooled-selected beta:
+
+| condition | selected beta | seed 0 | seed 1 | seed 2 |
+|---|---|---|---|---|
+| alpha=0.25 | 0.00 | 0/0/10 (trivial) | 0/0/10 (trivial) | 0/0/10 (trivial) |
+| alpha=0.50 | 1.00 | 6/3/1 (+0.030) | 3/5/2 (−0.101) | 7/2/1 (+0.087) |
+| alpha=0.75 | 0.50 | 4/6/0 (+0.002) | 6/3/1 (+0.085) | 4/2/4 (+0.006) |
+
+(mean Δ in parentheses.) At a common `beta = 0.75`:
+
+| condition | seed 0 | seed 1 | seed 2 |
+|---|---|---|---|
+| alpha=0.25 | 3/4/3 | 2/5/3 | 1/4/5 |
+| alpha=0.50 | 5/4/1 | 3/5/2 | 7/2/1 |
+| alpha=0.75 | 3/7/0 | 9/0/1 | 5/5/0 |
+
+The client-level response is seed-dependent at every alpha. At alpha=0.25 the response is
+predominantly negative at non-zero beta (support weighting degrades rare-class validation), whereas
+alpha=0.50/0.75 are mixed-to-positive. `N_ij` vs ΔF1 is non-monotonic everywhere. Client ids are
+per-seed realisations and are never pooled across seeds.
+
+---
+
+## I. Relation to RQ1 (support imbalance ↔ displacement ↔ rare-class performance)
+
+Observed, descriptive:
+
+- Realized support imbalance is highest at alpha=0.25 (mean class CV 1.302; `|S_j| < M` cells
+  16/27; 30 missing cells; client ratio 17.60) and lowest at alpha=0.75 (0.916; 4/27; 5; 6.31),
+  and mean prototype displacement follows the same ordering (2.919 / 2.340 / 1.385).
+  Directionally consistent across the three conditions.
+- Rare-class validation *levels* do **not** follow the same ordering (pooled means ≈ 0.76 / 0.65–0.69
+  / 0.78–0.81). Absolute cross-condition levels are not controlled because the training-derived
+  rare-class sets and per-client eval partitions differ.
+
+**No causal conclusion** is drawn: the association between support imbalance and displacement is
+mechanical under the beta formula, while the relationship to rare-class performance is confounded
+by which classes are rare and how much support they have in each partition.
+
+---
+
+## J. Relation to RQ2 (how beta changes prototypes and rare-class performance)
+
+- **Prototype position:** increasing beta moves every class prototype monotonically away from its
+  beta=0 equal mean (by construction, because supports are unequal); the magnitude grows with
+  support imbalance (mean class displacement at beta=1: 1.385 / 2.340 / 2.919 as imbalance grows).
+  `|S_j| = 1` would leave the aggregate unchanged, but no class has a single contributor at any of
+  these conditions.
+- **Rare-class performance:** the validation response is **non-monotone in beta** and
+  condition-dependent: overall declining at alpha=0.25 (best at beta=0), peaking at beta=1.00 at
+  alpha=0.50, peaking at beta=0.50 at alpha=0.75. The effect magnitude is comparable to or smaller
+  than between-seed variance at alpha=0.50/0.75; at alpha=0.25 the between-beta spread exceeds the
+  across-seed std, but the sample is only three seeds.
+
+---
+
+## K. Relation to RQ3 (does selected beta differ across non-IID conditions?)
+
+Yes, descriptively: the pooled-selected beta is **0.00 (alpha=0.25), 1.00 (alpha=0.50),
+0.50 (alpha=0.75)**. It is **not monotone** in alpha.
+
+Caveats that forbid a trend claim:
+
+- only **three** alpha levels and **three** project-defined seeds, **one** dataset;
+- one selection per condition, each statistically weak or only modestly stronger than seed noise,
+  and with **no tie-break** exercised at any condition;
+- the realized partitions differ, so the non-IID "condition" is only partially summarized by
+  alpha;
+- **no inferential monotonic-trend test** has been performed.
+
+RQ3 asks whether beta changes with conditions; it does not require a monotonic answer.
+
+---
+
+## L. Limitations
+
+- One dataset (5G-NIDD), three alpha values, three seeds; cross-dataset claims are deferred to
+  `CROSS_DATASET_BETA_ANALYSIS.md`.
+- The `S_j` participant/denominator rule remains a **REPRODUCTION ASSUMPTION** (material in
+  16/27 cells at alpha=0.25, 4/27 at alpha=0.50, 4/27 at alpha=0.75); all comparisons are
+  conditional on both modes sharing it.
+- Train/validation/test adaptation (70/10/20 stratified) differs from the paper's literal
+  80/20; the validation eval partition is a project decision.
+- **No inferential significance testing**; no global beta optimum. Each selected beta is
+  "best among the tested candidates under pooled validation for that condition".
+- Cross-alpha absolute metrics are not directly comparable because the rare-class sets, global
+  rare support, and per-client eval partitions differ by condition/seed; only within-condition
+  contrasts and relative patterns are interpreted.
+- Selecting beta=0 at alpha=0.25 makes the selected mode arithmetically the equal-`S_j` mean, so
+  that condition cannot show a benefit of support weighting.
diff --git a/docs/research/CROSS_DATASET_BETA_ANALYSIS.md b/docs/research/CROSS_DATASET_BETA_ANALYSIS.md
new file mode 100644
index 0000000..d9ddef5
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+++ b/docs/research/CROSS_DATASET_BETA_ANALYSIS.md
@@ -0,0 +1,240 @@
+# Cross-Dataset Beta Analysis: X-IIoTID vs 5G-NIDD (alpha = 0.25 / 0.50 / 0.75)
+
+Status: **descriptive six-condition comparison** of the frozen server-side prototype-aggregation
+beta protocol across two datasets and three Dirichlet non-IID levels, using only the audited
+condition-level pooled results:
+
+- X-IIoTID: Session 6 (`alpha=0.50`), Session 7 (`alpha=0.25`), Session 8 (`alpha=0.75`);
+- 5G-NIDD: Session 9 (`alpha=0.50`), Session 10 (`alpha=0.75`), Session 11 (`alpha=0.25`).
+
+This document runs nothing, uses **validation-only** selections, and makes **no causal, universal,
+or monotone** claim. Machine-readable counterpart:
+`artifacts/analysis/cross_dataset__matched_alpha_summary.csv` / `.json`,
+`artifacts/analysis/cross_dataset__beta_curve.csv`, plus the per-dataset
+`xiiotid__cross_alpha__*` and `5gnidd__cross_alpha__*` artifacts.
+
+Companion documents: `docs/research/XIIOTID_CROSS_ALPHA_ANALYSIS.md`,
+`docs/research/5GNIDD_CROSS_ALPHA_ANALYSIS.md`, `docs/research/EXPERIMENT_PROTOCOL.md`,
+`docs/research/DATASET_INSPECTION.md`, `docs/handoff/SESSION_HANDOFF.md`.
+
+---
+
+## A. Scope
+
+| Field | Value |
+|---|---|
+| datasets | X-IIoTID (`xiiotid`), 5G-NIDD (`5gnidd`) |
+| alpha | 0.25, 0.50, 0.75 (both datasets) |
+| seeds | 0, 1, 2 |
+| betas | 0.00, 0.25, 0.50, 0.75, 1.00 |
+| aggregation | `original_protean` + `support_weighted` |
+| conditions | 6 (2 datasets × 3 alphas × 3 seeds = 108 runs total across all sessions) |
+| selection | pooled validation-only per condition, seeds `{0,1,2}`; test read after fixing |
+| test_used_for_selection | false at all six conditions |
+
+Both datasets share the frozen training protocol (10 clients, 10 rounds, 3 local epochs, batch 256,
+Adam `lr=1e-3`, `mu=0.1`, `lambda=1.0`) and the same frozen preprocessing recipe; the only
+dataset-specific inputs are the raw CSV, label column, class mapping and dropped labels.
+
+---
+
+## B. Dataset structural differences
+
+| property | X-IIoTID | 5G-NIDD |
+|---|---|---|
+| benign label | `Normal` | `Benign` |
+| attack classes (8) | `C&C, Exfiltration, Exploitation, Lateral_movement, RDOS, Reconnaissance, Tampering, Weaponization` | `HTTPFlood, ICMPFlood, SYNFlood, SYNScan, SlowrateDoS, TCPConnectScan, UDPFlood, UDPScan` |
+| dropped label | `crypto-ransomware` | — |
+| training rows | 569,909 | 851,123 |
+| raw feature columns | 59 (56 numeric + 3 categorical) | 46 (41 numeric + 5 categorical) |
+| one-hot expanded width | 78 | 81 |
+
+The two **rare-set compositions are qualitatively different**, and this must be kept explicit:
+
+- 5G-NIDD rare classes are low-volume **flood/scan** categories (`ICMPFlood` is always rare;
+  partners vary: `SYNFlood`, `SYNScan`, `TCPConnectScan`, `UDPScan`, `HTTPFlood`, `SlowrateDoS`).
+- X-IIoTID rare classes are low-volume **behavioural** categories (`Tampering`, `Exfiltration`,
+  `Exploitation`, `Lateral_movement`, `C&C`, `Weaponization`, `Reconnaissance`, `RDOS`), whose
+  identities and per-seed unions vary more. A "rare class" is therefore not a comparable object
+  across the two datasets; only the protocol and the aggregation mechanism are shared.
+
+Both datasets have 9 classes (8 attack + benign) and all 10 clients have exactly two rare classes
+per seed, so all clients are eligible for rare-class evaluation.
+
+---
+
+## C. Matched-alpha realized heterogeneity
+
+`|S_j| < M` cells are summed over the three seeds (out of 27). Missing cells count `N_ij = 0`.
+
+| alpha | dataset | `|S_j|<M` cells | missing cells | client-size ratio mean | mean class-support CV | union unseen mean | max unseen/client |
+|---|---|---|---|---|---|---|---|
+| 0.25 | 5G-NIDD | 16 / 27 | 30 | 17.60 | 1.302 | 5.33 | 3 |
+| 0.25 | X-IIoTID | 19 / 27 | 38 | 14.75 | 1.442 | 5.67 | 4 |
+| 0.50 | 5G-NIDD | 4 / 27 | 4 | 9.59 | 1.225 | 1.33 | 1 |
+| 0.50 | X-IIoTID | 7 / 27 | 9 | 7.41 | 1.183 | 2.33 | 2 |
+| 0.75 | 5G-NIDD | 4 / 27 | 4–5 | 6.31 | 0.916 | 1.33 | 1 |
+| 0.75 | X-IIoTID | 3 / 27 | 4 | 4.67 | 0.881 | 1.00 | 1 |
+
+At every matched alpha the two datasets are **quantitatively close but not identical** in realized
+heterogeneity: X-IIoTID has slightly more missing class cells and a slightly higher support CV at
+alpha=0.25/0.50, while 5G-NIDD has a higher mean client-size ratio at alpha=0.25/0.50/0.75. Both
+datasets become far more homogeneous as alpha rises, with the mixture of `|S_j|<M` cells
+collapsing between alpha=0.25 and alpha=0.50.
+
+---
+
+## D. Pooled beta selection across six conditions
+
+Condition-level pooled selections (validation only):
+
+| dataset | alpha | selected beta | pooled validation mean | tie-break | curve shape |
+|---|---|---|---|---|---|
+| 5G-NIDD | 0.25 | **0.00** | 0.761453 | no | declines to 0.75, small rise at 1.0 |
+| 5G-NIDD | 0.50 | **1.00** | 0.692370 | no | rises to peak at 1.0, dip at 0.25 |
+| 5G-NIDD | 0.75 | **0.50** | 0.809081 | no | peaks at 0.50, declines both sides |
+| X-IIoTID | 0.25 | **0.00** | 0.591704 | no | monotone decreasing |
+| X-IIoTID | 0.50 | **0.75** | 0.579367 | no | rises to peak at 0.75 |
+| X-IIoTID | 0.75 | **0.50** | 0.476749 | no | peaks at 0.50, declines both sides |
+
+Observations:
+
+- **A common beta is selected by both datasets at alpha=0.25 (`0.00`) and alpha=0.75 (`0.50`)**;
+  they differ at alpha=0.50 (5G-NIDD `1.00` vs X-IIoTID `0.75`).
+- The selected beta is **not a function of alpha alone** and is **not universal**: across the six
+  conditions it takes the values `{0.00, 0.50, 1.00}`.
+- The alpha=0.25 result (`beta=0`, i.e. the equal-`S_j` mean) is the same descriptive outcome on
+  both datasets, but at the other two alphas the selections diverge, and no tie-break was ever
+  exercised.
+- All six pooled curves are non-monotone except X-IIoTID alpha=0.25 (monotone decreasing); the
+  between-beta spread is generally comparable to or smaller than the across-seed std (see the
+  per-dataset cross-alpha documents).
+
+Full pooled curves (validation per-client-mean rare-class macro-F1):
+
+| condition | beta 0.00 | 0.25 | 0.50 | 0.75 | 1.00 |
+|---|---|---|---|---|---|
+| 5G-NIDD a0.25 | **0.7615** | 0.7493 | 0.7257 | 0.7222 | 0.7376 |
+| 5G-NIDD a0.50 | 0.6872 | 0.6451 | 0.6747 | 0.6884 | **0.6924** |
+| 5G-NIDD a0.75 | 0.7781 | 0.7905 | **0.8091** | 0.7915 | 0.8043 |
+| X-IIoTID a0.25 | **0.5917** | 0.5887 | 0.5859 | 0.5795 | 0.5321 |
+| X-IIoTID a0.50 | 0.5444 | 0.5554 | 0.5673 | **0.5794** | 0.5735 |
+| X-IIoTID a0.75 | 0.4717 | 0.4744 | **0.4767** | 0.4725 | 0.4686 |
+
+---
+
+## E. Prototype displacement
+
+Cross-seed mean `||Cbar_j(1) − Cbar_j(0)||` (fixed round-0 snapshots, no retraining):
+
+| dataset | alpha=0.25 | alpha=0.50 | alpha=0.75 |
+|---|---|---|---|
+| 5G-NIDD | 2.919 | 2.340 | 1.385 |
+| X-IIoTID | 3.422 | 2.099 | 1.305 |
+
+Within each dataset, mean displacement decreases monotonically as alpha rises, tracking realized
+support imbalance. At matched alpha, 5G-NIDD has *smaller* mean displacement at alpha=0.25
+(2.919 vs 3.422) while X-IIoTID has slightly smaller displacement at alpha=0.50/0.75 (2.099 vs
+2.340; 1.305 vs 1.385). The per-class rank order is seed-sensitive and dataset-specific, and the
+**rare-class identities differ**, so these are not a like-for-like class comparison. Displacement
+is a direct-aggregation measure only; it is not interpreted as detection quality.
+
+---
+
+## F. Rare-class performance patterns
+
+Selected-beta test rare-class macro-F1 (mean ± sample std) vs `original_protean`:
+
+| condition | selected beta | test rare macro-F1 (selected) | test rare macro-F1 (original) | within-condition difference |
+|---|---|---|---|---|
+| 5G-NIDD a0.25 | 0.00 | 0.841236 ± 0.024202 | 0.842274 ± 0.025370 | −0.001039 |
+| 5G-NIDD a0.50 | 1.00 | 0.871984 ± 0.028501 | 0.880542 ± 0.037058 | −0.008558 |
+| 5G-NIDD a0.75 | 0.50 | 0.896738 ± 0.014470 | 0.879901 ± 0.023121 | +0.016837 |
+| X-IIoTID a0.25 | 0.00 | 0.632136 ± 0.047642 | 0.632790 ± 0.047152 | −0.000654 |
+| X-IIoTID a0.50 | 0.75 | 0.665503 ± 0.026685 | 0.642520 ± 0.028683 | +0.022983 |
+| X-IIoTID a0.75 | 0.50 | 0.605246 ± 0.085489 | 0.603890 ± 0.077764 | +0.001356 |
+
+**Do not compare absolute test levels across datasets or conditions.** The training-derived rare
+sets, global rare support and per-client eval partitions differ; 5G-NIDD rare macro-F1 levels
+(≈0.84–0.90) exceed X-IIoTID levels (≈0.60–0.67) largely because the rare classes are different
+and 5G-NIDD's are easier for nearest-prototype inference. Only the within-condition selected-vs-
+original difference is meaningful, and it is dominated by between-seed variance; the largest
+positive difference (+0.023 for X-IIoTID alpha=0.50) is still smaller than its between-seed std.
+No cross-dataset superiority is claimed.
+
+A consistent dataset-level observation: on 5G-NIDD test weighted-F1 is **below** accuracy (hard
+high-support classes), whereas on X-IIoTID weighted-F1 is **above** accuracy. This is a dataset
+characteristic, not a beta effect.
+
+At alpha=0.25 both datasets select `beta=0`, so at that condition the selected mode is
+arithmetically the equal-`S_j` mean and cannot demonstrate a benefit of support weighting.
+
+---
+
+## G. Client-level effects
+
+Improve/degrade/unchanged (validation, vs `beta=0`) at each condition's selected beta:
+
+| condition | selected beta | seed 0 | seed 1 | seed 2 |
+|---|---|---|---|---|
+| 5G-NIDD a0.25 | 0.00 | 0/0/10 | 0/0/10 | 0/0/10 |
+| 5G-NIDD a0.50 | 1.00 | 6/3/1 | 3/5/2 | 7/2/1 |
+| 5G-NIDD a0.75 | 0.50 | 4/6/0 | 6/3/1 | 4/2/4 |
+| X-IIoTID a0.25 | 0.00 | 0/0/10 | 0/0/10 | 0/0/10 |
+| X-IIoTID a0.50 | 0.75 | 7/3/0 | 8/1/1 | 8/1/1 |
+| X-IIoTID a0.75 | 0.50 | 6/4/0 | 9/0/1 | 6/4/0 |
+
+At the common `beta=0.75` (non-trivial comparison), the number of clients that improve (out of 10)
+is: 5G-NIDD **3 / 2 / 1** (a0.25), **5 / 3 / 7** (a0.50), **4 / 6 / 1** (a0.75); X-IIoTID
+**5 / 5 / 3** (a0.25), **7 / 8 / 8** (a0.50), **3 / 9 / 5** (a0.75). The broad shape is similar
+(mixed and seed-dependent), but the specific counts and mean deltas differ; at alpha=0.25, in
+particular, support weighting at `beta=0.75` helps more X-IIoTID clients than 5G-NIDD clients.
+`N_ij` vs ΔF1 is non-monotonic on both datasets. Client ids are per-seed realisations and are never
+pooled, so no client-level cross-dataset pairing is performed.
+
+---
+
+## H. RQ1 synthesis (support imbalance ↔ displacement ↔ rare-class performance)
+
+- On both datasets, realized support imbalance and mean prototype displacement move together with
+  alpha: higher alpha → lower CV / fewer missing cells / smaller displacement. Directionally
+  consistent across all six conditions.
+- Rare-class validation/test **levels** do **not** track the same ordering, on either dataset; they
+  are confounded by which classes are rare and their support in each partition.
+- The link between support imbalance and displacement is mechanical under the beta formula; the
+  link to rare-class performance is not established causally. **No causal conclusion.**
+
+## I. RQ2 synthesis (how beta changes prototypes and rare-class performance)
+
+- Increasing beta moves class prototypes monotonically away from the beta=0 equal mean, by an
+  amount that grows with realized support imbalance; this holds on both datasets.
+- Rare-class validation response is non-monotone in beta and condition-dependent on both datasets.
+  The effect is small relative to between-seed variance at most conditions.
+- At alpha=0.25 on **both** datasets the pooled validation optimum sits at `beta=0`, i.e. support
+  weighting gives no rare-class validation benefit under the strongest non-IID setting tested.
+
+## J. RQ3 synthesis (does selected beta differ across conditions/datasets?)
+
+- Across the six conditions the pooled-selected beta is `{0.00, 1.00, 0.50}` (5G-NIDD) and
+  `{0.00, 0.75, 0.50}` (X-IIoTID): it differs by condition and by dataset.
+- It is **not** a function of alpha alone (both datasets give identical selections at alpha=0.25 and
+  0.75 but differ at alpha=0.50), and it is **not** universal.
+- Caveats forbidding a trend/universality claim: two datasets, three alpha levels, three
+  project-defined seeds, six weak selections, no tie-break exercised, different rare-class
+  compositions, no inferential trend test.
+
+## K. Limitations
+
+- **Six conditions, two datasets, three project-defined seeds.** No inferential test; no global
+  optimum; each selected beta is "best among the tested candidates under pooled validation for that
+  condition".
+- The `S_j` participant/denominator rule remains a **REPRODUCTION ASSUMPTION**; it is material in
+  16/27 cells at 5G-NIDD alpha=0.25 and 19/27 at X-IIoTID alpha=0.25, and in ≤7/27 at the other
+  conditions. All comparisons are conditional on both modes sharing it.
+- **Rare-set composition differs by dataset** and is not comparable across datasets; absolute
+  metric levels are not comparable across conditions either.
+- Train/validation/test adaptation (70/10/20 stratified) differs from the paper's literal 80/20;
+  the validation eval partition is a project decision.
+- No `equal_available` control exists; `beta=0` is only arithmetically the equal-`S_j` mean.
+- **No cross-dataset causality or superiority**; **no monotone beta law**; the experiment grid is
+  complete as planned (two datasets × three alphas × three seeds × five betas + baseline).
diff --git a/docs/research/SESSION11_AUDIT.md b/docs/research/SESSION11_AUDIT.md
new file mode 100644
index 0000000..9c21471
--- /dev/null
+++ b/docs/research/SESSION11_AUDIT.md
@@ -0,0 +1,284 @@
+# Session 11 Post-Experiment Audit (5G-NIDD alpha=0.25)
+
+Status: **PASS.** Independent recomputation from machine-readable artifacts and the raw dataset
+confirms every Session-11 Stage-B claim for 5G-NIDD `alpha=0.25`, and re-confirms the prior
+condition labels used in the cross-alpha and cross-dataset reports. No discovered issue changes
+`beta_star` or the scientific interpretation. **No new training was run for this audit, no
+aggregation/model/preprocessing source changed, and no test-based selection occurred.**
+
+Audit performed: 2026-09-30. Audited HEAD: `bbd35085063194db58e4472e70b204d4be4a3607`.
+Machine-readable audit record:
+`artifacts/analysis/5gnidd__alpha0.25__multiseed__audit_recomputation.json`.
+
+Companion documents: `docs/research/5GNIDD_ALPHA025_BETA_VALIDATION.md`,
+`docs/research/5GNIDD_CROSS_ALPHA_ANALYSIS.md`, `docs/research/CROSS_DATASET_BETA_ANALYSIS.md`,
+`docs/research/5GNIDD_ALPHA050_BETA_VALIDATION.md`,
+`docs/research/5GNIDD_ALPHA075_BETA_VALIDATION.md`, `docs/research/XIIOTID_CROSS_ALPHA_ANALYSIS.md`,
+`docs/research/EXPERIMENT_PROTOCOL.md`, `docs/handoff/SESSION_HANDOFF.md`.
+
+---
+
+## A. Scope
+
+Independently verify the Session-11 claim for:
+
+- dataset `5gnidd`, alpha `0.25`, seeds `{0,1,2}`, beta `{0, 0.25, 0.5, 0.75, 1.0}` plus
+  `original_protean` (18 runs);
+- PRIMARY pooled-validation selection `beta_star = 0.00` using validation per-client rare-class
+  macro-F1 averaged within seed then across seeds;
+- `beta=0` equivalence class;
+- the 5G-NIDD three-alpha labels (0.25 = 0.00, 0.50 = 1.00, 0.75 = 0.50) and the six-condition
+  cross-dataset labels.
+
+The audit recomputed from run artifacts and raw data; it repeated no training and ran no new
+condition.
+
+---
+
+## B. Run inventory
+
+18 full-data runs enumerated from `results/5gnidd__alpha0.25__*/metadata.json` (15
+`support_weighted` + 3 `original_protean`), **18/18 present**, none duplicated, none partial, none
+unexpected. Each run contains all 14 expected artifacts; the round-0 prototype snapshot exists for
+all 18 runs. Metadata verified per run: dataset=5gnidd, alpha=0.25, seed, mode, clients=10,
+rounds=10, local_epochs=3, batch=256, lr=1e-3, mu=0.1, lambda=1.0, `manifest_reload_ok=true`,
+`smoke=false`. All 18 exit status 0. No other 5G-NIDD alpha run was created or modified
+(alpha=0.50 and alpha=0.75 each still contain exactly 18 runs); `equal_available` is absent from
+`src/`, `scripts/`, `tests/`.
+
+---
+
+## C. Pairing / manifest integrity
+
+Within each seed all six runs share one manifest content hash and a byte-identical round-0
+snapshot; `train_support_Nij.csv`, `characterization.csv` and `rare_unseen.csv` are identical
+across the six runs (one unique SHA-256 per file type per seed). `manifest_reload_ok = true` and
+`smoke = false` everywhere.
+
+| seed | manifest content hash | round-0 snapshot SHA-256 | support/char/rare unique counts |
+|---|---|---|---|
+| 0 | `ab6d8a8b63d478c4…` | `e2243ac4ed4391ff…` | 1 / 1 / 1 |
+| 1 | `74df102e4edb4509…` | `26a162991b7cbde9…` | 1 / 1 / 1 |
+| 2 | `061c094d1913f942…` | `e287bff5ca71f8d2…` | 1 / 1 / 1 |
+
+Each alpha=0.25 manifest was independently reproduced from the raw dataset
+(`prepare_dataset` → `reproduce_train_assignments`): exact `N_ij` match, partition-hash match and
+split-hash match for all three seeds; split sizes 851,123 / 121,589 / 243,177; 10 clients.
+Pairing is proven by content hashes, not filenames.
+
+---
+
+## D. Partition characterization audit
+
+Independently recomputed from the manifests; matches the report exactly:
+
+| statistic | seed 0 / 1 / 2 | reality (sum / mean) |
+|---|---|---|
+| `|S_j| < M` cells | 6 / 5 / 5 | **16 / 27** |
+| missing client-class cells | 10 / 10 / 10 | **30** |
+| client-size ratio | 9.93 / 27.83 / 15.05 | mean **17.60** |
+| union rare classes | 6 / 6 / 8 | 2 rare per client (all) |
+| union unseen classes | 6 / 5 / 5 | max 3 on a client |
+
+Mean class-support CV = **1.302**; maximum per-class `max/min` ratio across seeds = 185,504.
+
+---
+
+## E. Label / rare / unseen integrity
+
+- Cleaned 5G-NIDD label semantics reproduced: 1,215,890 raw rows, 1 duplicate dropped, 0 label
+  rows dropped, 9 classes (`Benign` + 8 attacks), benign index 0, 46 raw feature columns
+  (41 numeric, 5 categorical; 81 one-hot expanded).
+- Per-client rare/unseen recomputed from training `N_ij` (two smallest positive-support attack
+  classes, tie by class id) and compared to `rare_unseen.csv` across **all 18 runs**: **1,620 cells
+  checked, 0 mismatches**; benign class never flagged rare/unseen; rare and unseen never overlap;
+  every client has exactly two rare classes.
+- `evaluated_rare_classes` equals the training-derived union rare set (per seed); validation/test
+  labels did not influence rare identity.
+
+---
+
+## F. Validation metric recomputation
+
+Recomputed from raw artifacts (no report numbers copied):
+
+- seed-level primary score = mean over eligible clients of `val_per_client.csv`
+  `rare_class_macro_f1`; equals `val_selection.json` per-client-mean to **max diff 0.0** for all
+  15 runs; all 10 clients eligible in every seed.
+- global validation accuracy / macro-F1 / weighted-F1 recomputed independently from
+  `val_confusion_matrix.json` with the production formulas: **max diff 0.0** versus
+  `val_global_metrics.json`.
+
+---
+
+## G. Pooled-selection recomputation
+
+Computed from the independently recomputed seed-level scores (not from the report). Pooled = mean
+of the three seed means; std sample (`ddof=1`).
+
+| beta | pooled mean | sample std | recomputed selected |
+|---|---|---|---|
+| **0.00** | **0.761453** | 0.021903 | **yes** |
+| 0.25 | 0.749286 | 0.017107 | |
+| 0.50 | 0.725715 | 0.011017 | |
+| 0.75 | 0.722235 | 0.007967 | |
+| 1.00 | 0.737636 | 0.002756 | |
+
+- Recompute **matches the report** to formatting precision.
+- `argmax` = **0.00** (no tie; top-two gap ≈ 1.2e-2). `tie_break_used=false`.
+- Per-seed diagnostics reproduce **0.25 / 0.00 / 0.00**.
+
+---
+
+## H. Validation / test leakage audit
+
+- `run_baseline.py` derives `union_rare` from the training support matrix only; the
+  `val_selection` payload is built only from validation artifacts and records
+  `selection_split="validation"`, `test_used_for_selection=false` for all 15 `support_weighted`
+  runs (audited true).
+- `analyze_multiseed_beta.py` PRIMARY selection consumes only `per_seed_rows` built from
+  `val_selection.json`; test rows are read later and never referenced by selection or tie-break.
+  No code path sorts/filters candidates by a test field.
+- The audit's own `beta_star = 0.00` was reproduced from validation artifacts alone.
+
+Conclusion: selection is programmatic and validation-only; `test_used_for_selection = false` is
+upheld.
+
+---
+
+## I. Final test recomputation
+
+`beta_star = 0.00` fixed from pooled validation; only then test metrics read. Recomputed from
+`test_global_metrics.json` per seed (and cross-checked against `test_descriptive.csv`, max diff
+0.0), averaged across seeds with sample std:
+
+| metric | selected beta 0.00 (mean ± std) | original_protean (mean ± std) |
+|---|---|---|
+| rare-class macro-F1 | 0.841236 ± 0.024202 | 0.842274 ± 0.025370 |
+| rare-class recall | 0.961216 ± 0.031347 | 0.960556 ± 0.032423 |
+| macro-F1 | 0.816640 ± 0.013357 | 0.819405 ± 0.013919 |
+| accuracy | 0.730225 ± 0.019525 | 0.730968 ± 0.021431 |
+| weighted-F1 | 0.704463 ± 0.018175 | 0.705435 ± 0.020367 |
+
+Matches the report exactly. No superiority claim is made. The selected-beta and
+`original_protean` test means differ only by floating-point divergence (see §J), as expected when
+the selected beta is 0.
+
+---
+
+## J. `beta = 0` equivalence audit
+
+For seeds 0, 1, 2, `original_protean` vs `support_weighted beta=0`:
+
+| property | seed 0 | seed 1 | seed 2 |
+|---|---|---|---|
+| same manifest / split / hashes | yes | yes | yes |
+| round-0 snapshot byte-identical | yes | yes | yes |
+| support/characterization/rare_unseen identical | yes | yes | yes |
+| independent aggregation diff | 4.4e-16 | 4.4e-16 | 6.7e-16 |
+| history rare-macro-F1 round-0 diff | 0.0 | 0.0 | 0.0 |
+| history rare-macro-F1 max diff (rounds ≥ 1) | 2.17e-2 | 6.85e-2 | 2.74e-2 |
+| test metric max diff | 5.36e-3 | 5.39e-3 | 2.85e-3 |
+| classification | **B** | **B** | **B** |
+
+Class **B** (semantically equivalent + floating-point divergence); **no semantic discrepancy**.
+Equivalence remains conditional on the shared `S_j` reproduction assumption. Because the PRIMARY
+selection at this condition chose `beta=0`, the selected run *is* the `beta=0` run, so its test
+metrics differ from `original_protean` only by this divergence.
+
+---
+
+## K. Direct-effect audit
+
+Independently recomputed `||Cbar_j(beta) − Cbar_j(0)||` from the fixed round-0 snapshots with the
+production aggregation: each seed's `...__prototype_effect.csv` is produced by
+`analyze_prototype_effect.py` from the snapshot and the cross-seed pooled file aggregates it. Mean
+displacement at `beta=1.0` is **2.919** (monotone: 1.295 / 2.055 / 2.559 / 2.919 for
+beta 0.25/0.50/0.75/1.00). Displacement is a direct-aggregation measure only; no detection
+causality is inferred.
+
+---
+
+## L. Client-level audit
+
+At the selected `beta=0.00` the delta vs `beta=0` is trivially 0/0/10 for all seeds. At the common
+non-trivial `beta=0.75`, deltas recomputed from `val_per_client.csv` vs
+`client_validation_detail.csv` give improve/degrade/unchanged **3/4/3** (seed 0, mean −0.023),
+**2/5/3** (seed 1, mean −0.043), **1/4/5** (seed 2, mean −0.052). `N_ij` vs ΔF1 is non-monotonic.
+Client ids are per-seed realisations, not pooled.
+
+---
+
+## M. Cross-condition / cross-dataset labels
+
+Condition-level pooled selections confirmed from `selection_summary.json`:
+
+| condition | selected beta | tie-break | test_used_for_selection |
+|---|---|---|---|
+| 5G-NIDD alpha=0.25 (this session) | 0.00 | no | false |
+| 5G-NIDD alpha=0.50 (Session 9) | 1.00 | no | false |
+| 5G-NIDD alpha=0.75 (Session 10) | 0.50 | no | false |
+| X-IIoTID alpha=0.25 (Session 7) | 0.00 | no | false |
+| X-IIoTID alpha=0.50 (Session 6) | 0.75 | no | false |
+| X-IIoTID alpha=0.75 (Session 8) | 0.50 | no | false |
+
+The cross-alpha and cross-dataset reports make no causal, monotone, universal-beta or
+cross-dataset-superiority claim and explicitly state that selections differ descriptively.
+
+---
+
+## N. Artifact provenance
+
+| Reported quantity | Source artifact(s) | Derivation |
+|---|---|---|
+| run existence / config | `results/5gnidd__alpha0.25__*/metadata.json` | direct read |
+| manifest hashes / reproduction | `artifacts/partitions/5gnidd__alpha0.25__seed{0,1,2}.json` | module + `reproduce_train_assignments` |
+| pairing proof | `artifacts/analysis/..._prototype_snapshot.json` | sha256 across 6 runs/seed |
+| seed-level validation score | `results/.../val_per_client.csv` + `val_selection.json` | mean of per-client rare macro-F1 |
+| validation global metrics | `results/.../val_confusion_matrix.json` | independent numpy recompute |
+| pooled mean/std, `beta_star` | recomputed seed scores | mean/`stdev`, argmax |
+| test metrics | `results/.../test_global_metrics.json` + `..._test_descriptive.csv` | independent recompute + mean/std |
+| partition characterization | manifests + `..._partition_heterogeneity_*.csv` + `..._partition_characterization.csv` | independent numpy recompute |
+| beta=0 equivalence | original vs beta0 artifacts/snapshots | sha256 + independent aggregation + history diff |
+| direct-effect displacement | snapshots + `..._prototype_effect_pooled.csv` | production aggregation |
+| client improve/degrade | `results/.../val_per_client.csv` + `..._client_validation_detail.csv` | deltas vs beta=0 |
+| rare-class identity | `results/.../rare_unseen.csv` + manifest | recompute definition |
+| runtime / RSS | `artifacts/analysis/5gnidd__alpha0.25__multiseed__runtime.csv` (source `/tmp/opencode/5gnidd_alpha025_runtime.csv`) | parse `/usr/bin/time -v`; sum 68,798 s = 19.11 h |
+| cross-alpha table | `5gnidd__cross_alpha__*` (built from alpha0.25 + alpha0.5 + alpha0.75 multiseed artifacts) | read per-condition artifacts |
+| cross-dataset table | `cross_dataset__matched_alpha_summary.*` (built from both datasets' cross-alpha artifacts) | read per-dataset artifacts |
+
+---
+
+## O. Deviations / corrections found
+
+**None** affecting science. All Session-11 checks PASS. The only corrections made were to draft
+narrative text in the cross-dataset report (a client-count sentence was recomputed from the
+`cross_alpha_client_summary.csv` before the report was finalised); no number, artifact, or
+selection was affected. No training/aggregation/preprocessing source file was modified.
+
+---
+
+## P. Final audit verdict
+
+**PASS.**
+
+- Run inventory: **PASS** (18/18; no duplicates/partials; no legacy or extra 5G-NIDD run).
+- Pairing / manifest reproduction: **PASS** (hash-identical; raw-data reproduction exact incl.
+  partition hash).
+- Partition characterization: **PASS** (16/27, 30 missing, ratios 9.93/27.83/15.05, unseen 6/5/5).
+- Rare/unseen integrity: **PASS** (0 mismatches over 1,620 cells).
+- Validation recomputation (seed-level and global): **PASS** (exact).
+- Pooled selection: **PASS**; independent `beta_star = 0.00` using validation only.
+- Validation/test leakage: **PASS**.
+- Test summaries: **PASS** (exact).
+- beta=0 equivalence: **PASS**, class **B** for all seeds.
+- Direct-effect and client-level analyses: **PASS** (consistent with snapshots/artifacts).
+- Cross-condition labels: **PASS** (5G-NIDD 0.25/0.50/0.75 = 0.00/1.00/0.50; X-IIoTID
+  0.25/0.50/0.75 = 0.00/0.75/0.50; no causal or universal-beta claim).
+- Source/data integrity: **PASS**; `planningawal/` unchanged; both raw dataset SHA-256 unchanged;
+  `equal_available` absent; pytest **75 passed, 0 failed, 0 skipped**.
+
+The planned two-dataset × three-alpha experiment grid is **complete**. Session 11 is **safe to
+checkpoint** with the documented limitations (three project-defined seeds per condition, weak
+effects relative to seed variance, `S_j` reproduction assumption, `beta=0` selection at both
+alpha=0.25 conditions, no global-optimum claim).