{
  "source": "/benchmark/pangenome-reference-cv-20261014/inference-japanese/runs/NA18967/hprc",
  "source_complete_sha256": "9197821186cb73bd973ebdce7e70598d43596c6f60badc2874cd53672712c2a8",
  "source_evidence_sha256": "b8bebf0baec314457400eb889c7a15ecb02b3bb5cc254bc3aee6bcb44694621b",
  "code_sha256": {
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    "build_graph.py": "170765c3d0c53b3fc5bc9973016a17195937b9798e191dbacb08db124b94261a",
    "context_fragment.py": "098c19433935309ed05a2e3534ed514660c7af34baa3ce51928c3e6bca5ea6d6",
    "context_inference.py": "cb6007033d7d7320a26d8dc57283438385550949666e64e844363b159b66f7a0",
    "context_read_store.py": "6226eb83e37af78fcea04e17529f7cca8cd8e8b9e470b8ea5b0f5ad8a396eeee",
    "context_runtime_identity.py": "6d132df334e8ff31aeeb724808ed58aa8b7b7c264c97156ef89e9bdf52f115fb",
    "cv_references.py": "db687df88f0bc4e227c9b73242918629b1127d8ac80271c59056d703830ab126",
    "evidence_io.py": "14495b5ddbe02f4514f886424a4c75aa42ca5102fb78c1122ec903858a8b2289",
    "fragment_support.py": "bbfd8943563acccbb6b5ebda723d4c7cef44ef88a2dd508439cbae28cf52856f",
    "join_evidence.py": "e9e9c5ac6bcb0197436fd6403286595814f669261e5d4caf8069a11b467a4930",
    "joint_model.py": "c2279fd29e12f215e23fdd148fe7a6794b70fe8221d639c69c55e1ae6f87b5e4",
    "run_context_evidence.py": "3e99c6f7b95d4df77ae2598a59860caeb5adf059ce1be60f6a244053b0783d6a",
    "run_context_evidence_disk_v3.py": "779ad5b3833dbdfa074778515bb89dc789a857606204f378225ff888e4a94a9d",
    "run_context_inference.py": "3072b63da055bbd819ff57280e39431d2da611824059458336c0264062f3d6f5",
    "run_context_linear.py": "33ef894cf3a287ec3c52a32da50d50ea3c99f87446ce7c27144c5a6e573d2203",
    "score_native.py": "531340bcca991cd2fac6f563ae557a2882e9f75d5b3d4cd101161dc58a25eee2",
    "sequence_identity.py": "0152f515c50ce66f5dc58ad1442072b0093c247e4eca98949501d869a44cb721",
    "t1k_evidence.py": "b79c8cdf6708bf8f0401adb4a0aa9a73b8251da3543b5d6343382ac02a06b9b6",
    "test_context_inference.py": "2e2e6a2ae2ef5caa3bc2fff812656745f877b6b5100de6050f39babeb0c7ae89"
  },
  "script_sha256": "f1080946e5a29b4b384e0db73a18ca3c6398b41112779c240b85cc69a775285e",
  "native_table_sha256": "c38594828ca75a716e3e518cf38e54e87c837895d91db2a683cb2f5faa126821",
  "aliases_sha256": "c722054e4c2fe96c51f4776b0089cfc399e4e592b77e793c240b8d7e070e0447",
  "job_id": "54049143",
  "graph_sequences_absent_from_native_catalogue": 0,
  "native_panel_aliases_retained": 468,
  "truth_loaded": false,
  "intervention": "Drop non-IPD-prefixed candidate placements before normalization; retain native panel aliases",
  "limitations": [
    "Existing original.fa/flanked reference configuration, not a full-genomic-IPD rebase.",
    "Tests incremental graph retrieval over native retrieval, not all possible graph algorithms.",
    "Candidate availability is held equal; retrieved candidates may differ by design.",
    "Same scorer, fallback and decision thresholds as original union replay."
  ],
  "retrieval_counts": {
    "fragments": 873984,
    "native_supported_fragments": 15249,
    "graph_supported_fragments": 15713,
    "graph_only_fragments": 4754
  },
  "status": "native_proposal_ablation_complete",
  "output_sha256": {
    "E1/calls.json": "9fa04cb1e940f534b291ba7064fb7fe510042d434173226cb0b3eb657c1b87ec",
    "E1/decisions.json": "c172b22489dd131b7a10e3b0b07760e731439a37ad5cf5b2f12b2bba8f866a01",
    "E1/sequence_calls.json": "e237eaebed882720edc701a8eb32a172d75eb3b1988723e17ded74b404235d6c",
    "E2/calls.json": "68e7a70c4e3fa15f23c0aa653d6c27785411fb77a180f93efa5132baf58fb5b5",
    "E2/decisions.json": "e3c7441b9138191ba7c9414024031bb543c634ec788bbb9fec806d2e5940148a",
    "E2/sequence_calls.json": "1719a365b0777db72c8f562b928ffd1ebd6ad10e5b3dd0e5e2c391a3dd6a3086",
    "E3/calls.json": "e1503fe7b46abdd64136b923060fbb9a3c787ab01c8bd9fee7b74db5aa482d8e",
    "E3/decisions.json": "676913cd009714994439a284f4434ca5f157ffa4dc5fd4f9e74cb73c808ecb8e",
    "E3/sequence_calls.json": "6c2f122968873fbf1ba4c1c23b21bc56981b6813836df07712f85b7c4b8a1fa5"
  }
}
