Seal Phase 4AJ fixed APL timing hypothesis audit
This commit is contained in:
Digital Drosophila Archive
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{
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"timestamp_utc": "2026-09-30T03:14:10.691689+00:00",
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"sources": {
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"PROTOCOL.md": "d96aef0107f7b0791d16e475b749da418b8a38d2c56a94e0779de0cd6581a7de",
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"al_origin_audit.py": "7201871477a29ede31c7d6c6bf1c92700da3db5505e67ccfa7cb43126b8464b9",
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"calibration.py": "fb15ddeaa108305c8de697bbae36b23ab0414a7c58db51c66dce9feb4a048a0d",
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"compare_timing.py": "9010f070fba9b7c9cf2d86187ee2abc57f3ac606ebc08a42baad4f3922b51734",
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"config.json": "0b720e23aa7988b2b443e14951082b1ce9b061a183b7f858c0e0f3c0fc6fb25e",
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"context.py": "06d4994af3729d653263391ff3a3604f7c919e78562604e5c86acfa292d60ba0",
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"finalize.py": "0a2dbf9e5f889e9dd3491d036e6f92c17417a84482c5e1e49134c0993f7d68f2",
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"gpu_timing.py": "af1975ba5e5e700208c0a598d3cbe648a3cf10885c6231239b6e4b28f76d173b",
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"oracle_timing.py": "39d8c47c94bc2faddf016864a43e7715907fb987f56f7b27098060a88851f6be",
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"prepare.py": "bba71bcd52dcb78d9ae0fa93a8a43173a4669ecef038dce18ce7d82edd9bce50",
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"run_case.py": "d93e4fe2df542ce5a0f0adb5aceada583dc8c921f0159f426e50428d79d67a1d",
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"run_suite.py": "6f26c626acf9ef8e6fae7902af0cbf0bd176eb322529ca8aa203a9700716c889",
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"shift_audit.py": "46f380dac340acc91f226968bb493475a31777f8290fb20f9145a97c9009d845",
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"test_al_origin_audit.py": "4b75a39d36090b0a66cc7ad4b370ac785713fb58c366df2efcc55152d612fc2b",
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"test_calibration.py": "307a2848bf6d05aaa8105bb3558be2a74425894f96a4a2bd20af8b82cb8b6e25",
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"test_protocol.py": "cbae93c993ac9aa99bcce68ae2131c7f938f8a63e89779f8d3d79e36bf268dee",
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"tests/__init__.py": "bfc0d9e17410c2c52ea1d9a5259c92964f16b118dbae8cecad258697b67e4bdc",
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"tests/test_compare_timing.py": "71876b36eef88c198aa8e833af547dbe772001c71b010707b656c165c8b54031",
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"tests/test_timing_queue.py": "4a375444dc732c3538df8aa4b81e43b5418754fcebebb0d02c16faad03d43195",
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"timing_queue.py": "54df6d4818e2a0c26e96fb0aaf5d9b71cd964981706da937562d48af79aca14e",
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"verify_frozen.py": "97d8a240b08baaca935f9c0278978883005dcd6fdbb4ca0d948074ef79fd349c"
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},
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"config": {
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"phase": "4AJ",
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"name": "apl-timing-lab-v1",
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"human_authorization": "允许独立新模型分支测试动力学假设",
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"gpu_uuid": "GPU-79f3a85d-adce-7833-7003-6488140ca596",
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"neurons": 166700,
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"edges": 25582938,
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"raw_weight_sum": 124177617,
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"delays_steps": [
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0,
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18
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],
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"dt_ms": 0.1,
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"apl": {
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"tau_ms": 20.0,
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"gain": 0.01,
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"normalization": 1.0
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},
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"fixtures": [
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"zero",
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"pn_pulse",
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"kc_ref_boundary",
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"two_sources",
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"arrival_collision",
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"natural_request",
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"apl_only",
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"high_fanin"
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],
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"fixture_repeats": 3,
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"calibration": {
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"split": "calibration",
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"odor_count": 6,
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"modes": [
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"physiological",
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"matched_energy"
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],
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"seeds": [
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51101,
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51102,
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51103,
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51104,
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51105
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],
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"duration_ms": 100.0,
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"median_scope": "original frozen 12-odor panel",
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"full_oracle_probes": [
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"cal-physiological-00-s51101",
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"cal-matched_energy-00-s51101"
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],
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"repeat_first_seed_each_odor": true
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},
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"gates": {
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"sparse_min_fraction": 0.03,
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"sparse_max_fraction": 0.09,
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"max_fraction_strict": 0.5,
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"min_fraction_strict": 0.0,
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"minimum_separable_odor_pairs": 3,
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"same_jaccard_gt_between": true,
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"between_euclidean_gt_within": true,
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"both_modes_required": true,
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"finite_required": true,
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"repeat_exact_required": true
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},
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"output_budget_bytes": 25769803776,
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"origin_audit_budget_bytes": 2147483648,
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"training": false,
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"heldout_dynamic_access": false,
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"candidate_generation": false,
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"hypothesis": "Only delay the entire generated graded-APL h by 18 exact steps; zero delay is a fresh replay of sealed AG control. Engineering scheduling parity, not measured MaleCNS physiology. No change to I/O, gain, state update, fast-APL zero mask, neuron coefficients, inputs or biological observation window.",
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"tail_contract": "pending tail is the next D queue slots, shape(D,4064); if T<D its initial zero prefix is not generated future output. Do not advance the brain or APL after the original window. Closed-loop h totals are not forced to match.",
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"selection_policy": "Both arms and all fixed CAL cases retained regardless of representation outcome. Stop later scientific execution on numerical/oracle/integrity failure. No scan, tuning, favorable seed or result selection."
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},
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"inputs": [
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{
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"path": "experiments/phase4ai-pn-recruitment-audit/manifest.json",
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"sha256": "12c6f2e9929b3f7084e8b39b90c8851185febbc0afbb7031f9eebb4c41d2731d"
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},
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{
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"path": "experiments/phase4ai-pn-recruitment-audit/checksums.sha256",
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"sha256": "2a6247fb9a9fd187cc29dee03e41f98aa6c859a1edc58bc02a2062f8ee09f848"
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},
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{
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"path": "models/male-cns-lif/pn-recruitment-audit-v1/manifest.json",
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"sha256": "a53443ac124e9bebc813867a5015d77276c2bd3edf89cd606a57d54756fe0dd7"
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},
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{
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"path": "experiments/phase4ag-author-apl-r2/manifest.json",
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"sha256": "21593297c40bee58516d4d7fd16e9d8d20ffdea5f8e0652fa5dd4e903b4d96ee"
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},
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{
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"path": "models/male-cns-lif/author-apl-lab-v2/manifest.json",
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"sha256": "208c00961b9d895d14ac050bc23fbc18db49d0df1fcf5c20d4c3eaa8e15ff7ff"
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},
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{
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"path": "datasets/male-cns-v1.0/processed/neuron-only/neuron-index/unified-metadata.parquet",
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"sha256": "922af16846a065c3dbfca7c11146b83ca217fcbd7392edc745f444a04eae8c63"
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},
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{
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"path": "experiments/phase4af-author-fullgraph/oracle/no_input/coefficients.json",
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"sha256": "bde79d95ef0097b827d5faf4d5658eafc009d8e9fcef1fddd645c953823e3f64"
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},
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{
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"path": "models/male-cns-lif/kc-drive-audit-v1/replay_core.py",
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"sha256": "aa3187cb23712c09ab603e27e60424294db92de8086d60a95cf7a629d0521fdc"
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},
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{
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"path": "models/male-cns-lif/author-apl-lab-v2/legacy_apl_worker.py",
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"sha256": "21ceec65fe42581dc55872010e0025d660e80358905f1cf4df1dadf341a3b291"
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},
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{
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"path": "models/male-cns-lif/author-apl-lab-v2/gpu_apl.py",
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"sha256": "69f5d893f47dafff4ef7c3186c3df0b9014666b32c8f4e943b57016bec92b18a"
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},
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{
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"path": "models/male-cns-lif/author-apl-lab-v2/oracle_apl.py",
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"sha256": "357a7d3debb5abc34a8714c0233b456547a154d9d5855d28661b4f01019a80ea"
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},
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{
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"path": "models/male-cns-lif/author-apl-lab-v2/compare.py",
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"sha256": "6e1616b086f667fa4e4b5087f500f8080281977ca9922e7b055acfddd2003bd5"
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},
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{
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"path": "models/male-cns-lif/author-apl-lab-v2/calibration.py",
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"sha256": "edb9cb2d890471fd07afd88c959ef3540b0cd40af490fac3f26396b5e7f5bf9c"
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},
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{
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"path": "models/male-cns-lif/author-apl-lab-v2/validate_components.py",
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"sha256": "5cfc9a4505da6b8fb4e7d2617cdaedaa8475ed46a11ec9bdf0d4d25b1d22c2d3"
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},
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{
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"path": "experiments/phase4ai-pn-recruitment-audit/protocol/neuron-source-groups.parquet",
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"sha256": "8aac9e262ba4666ba2a4fd69ee3c51c3e94c694971cdba186b0c7ce242a7b974"
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}
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],
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"parent_commit": "8d6b063aafebf936d6c4dcfd0064a6428fd4dd0b",
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"before_new_trajectories": true,
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"prior_CAL_and_AI_outcomes_known": true,
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"single_factor": "generated graded-APL h applied at t versus t+18; nothing else",
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"fixed_input_counts_and_amplitudes": true,
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"actual_accepted_requests_may_change_due_to_closed_loop": true,
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"formal_learning_claim": false,
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"oracle_limit": "Independent Brian LIF state with shared legacy Torch APL arithmetic; separate component audit",
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"delay_biological_measurement": false,
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"whole_brain_equal_total_inhibition_claim": false,
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"timing_test_no_full_future_tail_claim": true,
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"source_diffs_are_review_material_not_equivalence_proof": true,
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"scope": "Origin audit -> exact shift conservation -> two-arm fixtures -> fullgraph oracle probes -> complete two-arm fixed CAL -> frozen regression",
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"python": "3.10.12 (main, Aug 31 2026, 10:18:17) [GCC 11.4.0]",
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"numpy": "2.2.6",
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"machine": "x86_64"
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}
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