Document data-provider review and privacy assessment

CHECKSUMS_SHA256.txt

@@ -12,7 +12,7 @@ ef32375fae0bdec981f173bc618360bea4e9a2c399fa57265c86d57fb1766ac3  data/processed
 8b4b2237e13b4a39a8d948ddd9c9bbe9c6cb68f32a6b58c67a4093bca1d353e0  data/processed/normalized_cleaned.parquet
 a037706bee3eae6ddebc709c2343a91dbf3c2d28be67ea2012a180391de74639  data/processed/valid_indices.csv
 96ada0dcfef13f89e1ab3b096e8d77ac129d3905421f1a5621bd82142b027dd0  LICENSE_OR_USAGE_NOTES.md
-c84e9ae79270bb36882559ef7e2ed3d87452035de4f30b449669ba37d805bc59  MANIFEST.csv
+271c2e6ab38f757e9dd4c2730517f3fd7a497a77ac7f4c9d8f77b75b01526044  MANIFEST.csv
 0be665f3ec913c54623e61b7cc17836e3cedd5cafd49ea2c72a462dd66031dc9  metadata/active_experiment_config.json
 ab23f1170985390b129b6ffa0d5ba7528111938ba1a5684f3b453a3129ac0753  metadata/bandit_instances/cyclic_5s__final_embedding_divisor_hidden_512__linearized__f7d2fe4d2f94833d.json
 b832d1e4ed75c0917ceda28aaeed00fee827cbdcd3679cbf20d40568298f5f3e  metadata/cyclic_replay_5s_config_with_beta.json
@@ -22,6 +22,6 @@ b832d1e4ed75c0917ceda28aaeed00fee827cbdcd3679cbf20d40568298f5f3e  metadata/cycli
 4d3d4271e407cf724fba8e8af10955e3b8c8f4a1a47832fc377a3966ad8dc683  metadata/final_embedding_divisor_hidden_512/learned_embeddings.npy
 548fbbf3398c4073dca3d1ea7a91ff08cfeebc6c9c3a5e1fec2c0ae35291368d  metadata/final_embedding_divisor_hidden_512/meta.json
 5ec2f22421d3475b18e39829e8ce4ed2fc930cbec848a28116c3b11f58537897  provenance_public.md
-3e89220219854ad37b9ca58df9a841a4a963b73b230a0985fe5d5962d9c59ef6  README.md
+da838a771cafc18c6f8e8fd2126b7c9a454a3c11b6a2b7f8ab586670bf365688  README.md
 a2cd894dffef44b771d09703242bd68e7f91bded083132ed9660b66f8d850348  sensor_locations/gq_sensor_locations_active_nodes.csv
 9c7575c6a1396beab04a180327fca783ca4d87b8e96d14a2af7d3e9ba42b1843  sensor_locations/gq_sensor_locations_source.csv

MANIFEST.csv

@@ -22,6 +22,6 @@ metadata/cyclic_replay_trim_points.json,metadata,Replay/Markov-chain metadata fo
 metadata/final_embedding_divisor_hidden_512/learned_embeddings.npy,derived_model,Derived embedding/reward model artifact used to construct the bandit rewards.,92545760,4d3d4271e407cf724fba8e8af10955e3b8c8f4a1a47832fc377a3966ad8dc683,2026-04-26T04:27:24.939331+00:00,learned_embeddings.npy,yes,
 metadata/final_embedding_divisor_hidden_512/meta.json,derived_model,Configuration or portable replay/mixing metadata.,1386,548fbbf3398c4073dca3d1ea7a91ff08cfeebc6c9c3a5e1fec2c0ae35291368d,2026-09-12T18:04:14.495842+00:00,meta.json,no,Generated/sanitized public metadata.
 provenance_public.md,documentation,Public dataset documentation.,3545,5ec2f22421d3475b18e39829e8ce4ed2fc930cbec848a28116c3b11f58537897,2026-09-12T19:06:53.457058+00:00,,no,Generated/sanitized public metadata.
-README.md,documentation,Public dataset documentation.,6776,3e89220219854ad37b9ca58df9a841a4a963b73b230a0985fe5d5962d9c59ef6,2026-09-12T19:06:44.963373+00:00,,no,Generated/sanitized public metadata.
+README.md,documentation,Public dataset documentation.,7313,da838a771cafc18c6f8e8fd2126b7c9a454a3c11b6a2b7f8ab586670bf365688,2026-09-12T19:34:42.613104+00:00,,no,Generated/sanitized public metadata.
 sensor_locations/gq_sensor_locations_active_nodes.csv,sensor_locations,Active 9-node sensor GPS table after applying DROP_NODES=[6].,374,a2cd894dffef44b771d09703242bd68e7f91bded083132ed9660b66f8d850348,2026-09-12T15:33:21.411245+00:00,nodes_gps.csv,filtered_rows,Rows filtered to active paper nodes only; coordinate values unchanged.
 sensor_locations/gq_sensor_locations_source.csv,sensor_locations,Source sensor GPS table used by preprocessing; node 6 is recorded but excluded from the paper instance.,419,9c7575c6a1396beab04a180327fca783ca4d87b8e96d14a2af7d3e9ba42b1843,2025-08-13T13:19:05.629519+00:00,nodes_gps.csv,yes,

README.md

@@ -48,6 +48,19 @@ This dataset was approved for public release under:
 
 Distribution Statement A. Approved for public release; distribution is unlimited.
 
+### Data Provider / Public-Release Approval
+
+The released sequence was reviewed and approved by the relevant data provider
+for public release.
+
+### Sensitive Content and Privacy
+
+The data come from an instrumented vehicle-tracking experiment. No
+human-subject data were intentionally collected. The release contains raw
+acoustic recordings and precise vehicle and sensor GPS coordinates. The
+released recordings were reviewed for incidental intelligible speech and
+personally identifiable or sensitive content, and none was identified.
+
 No separate standard open-source or Creative Commons license is asserted by
 this dataset card. See `LICENSE_OR_USAGE_NOTES.md` for the approved usage notes.