{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:2L4VMQARWNIAPTJPNAW63XHIAC","short_pith_number":"pith:2L4VMQAR","canonical_record":{"source":{"id":"2605.24699","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-23T18:36:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"936da72cb524cb2db1203b2b1bee900f65f6cfe3de68c4a0be16a17a046d9357","abstract_canon_sha256":"7166bad814874b0613f6917197d1473af2e545455acf715dce9508f10761a49c"},"schema_version":"1.0"},"canonical_sha256":"d2f9564011b35007cd2f682deddce800aa193d71865e6434fdd195fcf647421b","source":{"kind":"arxiv","id":"2605.24699","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.24699","created_at":"2026-05-26T01:03:53Z"},{"alias_kind":"arxiv_version","alias_value":"2605.24699v1","created_at":"2026-05-26T01:03:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.24699","created_at":"2026-05-26T01:03:53Z"},{"alias_kind":"pith_short_12","alias_value":"2L4VMQARWNIA","created_at":"2026-05-26T01:03:53Z"},{"alias_kind":"pith_short_16","alias_value":"2L4VMQARWNIAPTJP","created_at":"2026-05-26T01:03:53Z"},{"alias_kind":"pith_short_8","alias_value":"2L4VMQAR","created_at":"2026-05-26T01:03:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:2L4VMQARWNIAPTJPNAW63XHIAC","target":"record","payload":{"canonical_record":{"source":{"id":"2605.24699","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-23T18:36:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"936da72cb524cb2db1203b2b1bee900f65f6cfe3de68c4a0be16a17a046d9357","abstract_canon_sha256":"7166bad814874b0613f6917197d1473af2e545455acf715dce9508f10761a49c"},"schema_version":"1.0"},"canonical_sha256":"d2f9564011b35007cd2f682deddce800aa193d71865e6434fdd195fcf647421b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T01:03:53.880093Z","signature_b64":"+ePsmtG4674SGdMzdHPMU/+ChU4vsknk8UYCDZgzfnJdEvR6QPX24X9wwt2JL4TFQEsQ86E2FU+C0I2X8h8cBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d2f9564011b35007cd2f682deddce800aa193d71865e6434fdd195fcf647421b","last_reissued_at":"2026-05-26T01:03:53.879295Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T01:03:53.879295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.24699","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-26T01:03:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"re8PRJ1d3gChgM0iaRrWSPwnpsPKI5nG28XGEWlZr0sF4vIbKH3KPdZzhdr0TNvGwYTUJxrMPou3Kucn3ZfrBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T04:37:41.925095Z"},"content_sha256":"4816566ad04c9c906927eca5c0eb591b03ce3511e0025d30707d8e85ebbabb5b","schema_version":"1.0","event_id":"sha256:4816566ad04c9c906927eca5c0eb591b03ce3511e0025d30707d8e85ebbabb5b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:2L4VMQARWNIAPTJPNAW63XHIAC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MDIA: A Multi-Agent Diagnostic Intelligence Pipeline on HealthBench Professional","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AI","authors_text":"David Rey-Blanco, Roberto Cruz","submitted_at":"2026-05-23T18:36:58Z","abstract_excerpt":"Most reported gains on agentic-LLM clinical benchmarks are often attributed to prompt engineering, yet our results suggest that larger improvements can come from architectural and engine-level design. We present MDIA, a Multi-agent Diagnostic Intelligence Agent implemented as a 7-node specialty-routed clinical reasoning graph, on the full HealthBench Professional benchmark (n = 525), on a non-fine-tuned LLM. MDIA achieves 0.6272 under OpenAI's GPT-5.4-2026-03-05, which is +3.72 pp above the performance of OpenAI's ChatGPT for Clinicians. The experimental work shows that performance lift is att"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.24699","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.24699/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-26T01:03:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nB2CNwTD4Edf/MRasQ2U9pZoyUXZ7oOHVLbq37raRhoAa0e0QwRIBHQqGUbPpJd9ezzxJWXg4/2VRCiifetoAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T04:37:41.925469Z"},"content_sha256":"f4744bc9995f873fe8e6d5966a730d44e25aa7ada4ad5e38a12885b06efc326e","schema_version":"1.0","event_id":"sha256:f4744bc9995f873fe8e6d5966a730d44e25aa7ada4ad5e38a12885b06efc326e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2L4VMQARWNIAPTJPNAW63XHIAC/bundle.json","state_url":"https://pith.science/pith/2L4VMQARWNIAPTJPNAW63XHIAC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2L4VMQARWNIAPTJPNAW63XHIAC/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-28T04:37:41Z","links":{"resolver":"https://pith.science/pith/2L4VMQARWNIAPTJPNAW63XHIAC","bundle":"https://pith.science/pith/2L4VMQARWNIAPTJPNAW63XHIAC/bundle.json","state":"https://pith.science/pith/2L4VMQARWNIAPTJPNAW63XHIAC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2L4VMQARWNIAPTJPNAW63XHIAC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:2L4VMQARWNIAPTJPNAW63XHIAC","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"7166bad814874b0613f6917197d1473af2e545455acf715dce9508f10761a49c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-23T18:36:58Z","title_canon_sha256":"936da72cb524cb2db1203b2b1bee900f65f6cfe3de68c4a0be16a17a046d9357"},"schema_version":"1.0","source":{"id":"2605.24699","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.24699","created_at":"2026-05-26T01:03:53Z"},{"alias_kind":"arxiv_version","alias_value":"2605.24699v1","created_at":"2026-05-26T01:03:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.24699","created_at":"2026-05-26T01:03:53Z"},{"alias_kind":"pith_short_12","alias_value":"2L4VMQARWNIA","created_at":"2026-05-26T01:03:53Z"},{"alias_kind":"pith_short_16","alias_value":"2L4VMQARWNIAPTJP","created_at":"2026-05-26T01:03:53Z"},{"alias_kind":"pith_short_8","alias_value":"2L4VMQAR","created_at":"2026-05-26T01:03:53Z"}],"graph_snapshots":[{"event_id":"sha256:f4744bc9995f873fe8e6d5966a730d44e25aa7ada4ad5e38a12885b06efc326e","target":"graph","created_at":"2026-05-26T01:03:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2605.24699/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most reported gains on agentic-LLM clinical benchmarks are often attributed to prompt engineering, yet our results suggest that larger improvements can come from architectural and engine-level design. We present MDIA, a Multi-agent Diagnostic Intelligence Agent implemented as a 7-node specialty-routed clinical reasoning graph, on the full HealthBench Professional benchmark (n = 525), on a non-fine-tuned LLM. MDIA achieves 0.6272 under OpenAI's GPT-5.4-2026-03-05, which is +3.72 pp above the performance of OpenAI's ChatGPT for Clinicians. The experimental work shows that performance lift is att","authors_text":"David Rey-Blanco, Roberto Cruz","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-23T18:36:58Z","title":"MDIA: A Multi-Agent Diagnostic Intelligence Pipeline on HealthBench Professional"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.24699","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:4816566ad04c9c906927eca5c0eb591b03ce3511e0025d30707d8e85ebbabb5b","target":"record","created_at":"2026-05-26T01:03:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"7166bad814874b0613f6917197d1473af2e545455acf715dce9508f10761a49c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-23T18:36:58Z","title_canon_sha256":"936da72cb524cb2db1203b2b1bee900f65f6cfe3de68c4a0be16a17a046d9357"},"schema_version":"1.0","source":{"id":"2605.24699","kind":"arxiv","version":1}},"canonical_sha256":"d2f9564011b35007cd2f682deddce800aa193d71865e6434fdd195fcf647421b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d2f9564011b35007cd2f682deddce800aa193d71865e6434fdd195fcf647421b","first_computed_at":"2026-05-26T01:03:53.879295Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T01:03:53.879295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+ePsmtG4674SGdMzdHPMU/+ChU4vsknk8UYCDZgzfnJdEvR6QPX24X9wwt2JL4TFQEsQ86E2FU+C0I2X8h8cBA==","signature_status":"signed_v1","signed_at":"2026-05-26T01:03:53.880093Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.24699","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4816566ad04c9c906927eca5c0eb591b03ce3511e0025d30707d8e85ebbabb5b","sha256:f4744bc9995f873fe8e6d5966a730d44e25aa7ada4ad5e38a12885b06efc326e"],"state_sha256":"c5490a96326f57c836b87e70efd554d740f772fb36e6109181a4475128244bba"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aDfVVBvdKkeCJY1SJ9G8wr0rKOnw0qIvmVegeg6o7Chq1sQ5vHfHVrgiWK1qPyi9kiuvL7DHbVCZq1oSqlqxBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-28T04:37:41.927513Z","bundle_sha256":"a959ffcb4d8b174e37d948ffc4cc7abd113362a705325884068670c09b9a52dd"}}