{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:CAYSQSS5XQVH2T3MRZ5L33U7VU","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":"5b7a2156e03db5aea8f348daeced33720f1cffc4e879c108ba6297d6e94ad2c8","cross_cats_sorted":["cs.CL","stat.ME"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-01-14T02:04:34Z","title_canon_sha256":"cf215403b4e4204f58caf15b04de2ba092dab0b04af68f0db9f37ac620087a22"},"schema_version":"1.0","source":{"id":"2601.09072","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.09072","created_at":"2026-06-11T01:09:26Z"},{"alias_kind":"arxiv_version","alias_value":"2601.09072v1","created_at":"2026-06-11T01:09:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.09072","created_at":"2026-06-11T01:09:26Z"},{"alias_kind":"pith_short_12","alias_value":"CAYSQSS5XQVH","created_at":"2026-06-11T01:09:26Z"},{"alias_kind":"pith_short_16","alias_value":"CAYSQSS5XQVH2T3M","created_at":"2026-06-11T01:09:26Z"},{"alias_kind":"pith_short_8","alias_value":"CAYSQSS5","created_at":"2026-06-11T01:09:26Z"}],"graph_snapshots":[{"event_id":"sha256:c4ede73685b32a213726458a27ec1beb9db0d596b930bc2fdbf2ae2a5d92ddef","target":"graph","created_at":"2026-06-11T01:09:26Z","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/2601.09072/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Developing safe, effective, and practically useful clinical prediction models (CPMs) traditionally requires iterative collaboration between clinical experts, data scientists, and informaticists. This process refines the often small but critical details of the model building process, such as which features/patients to include and how clinical categories should be defined. However, this traditional collaboration process is extremely time- and resource-intensive, resulting in only a small fraction of CPMs reaching clinical practice. This challenge intensifies when teams attempt to incorporate uns","authors_text":"Aaron Kornblith, Andrew Bishara, Avni Kothari, Chandan Singh, Jean Feng, Lucas Zier, Newton Addo, Patrick Vossler, Yan Shuo Tan","cross_cats":["cs.CL","stat.ME"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-01-14T02:04:34Z","title":"Human-AI Co-design for Clinical Prediction Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.09072","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":"sha256:713fa0d5fda93210750152776de37e430d9c051b5ce3ccdad3d8aaba026df250","target":"record","created_at":"2026-06-11T01:09:26Z","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":"5b7a2156e03db5aea8f348daeced33720f1cffc4e879c108ba6297d6e94ad2c8","cross_cats_sorted":["cs.CL","stat.ME"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-01-14T02:04:34Z","title_canon_sha256":"cf215403b4e4204f58caf15b04de2ba092dab0b04af68f0db9f37ac620087a22"},"schema_version":"1.0","source":{"id":"2601.09072","kind":"arxiv","version":1}},"canonical_sha256":"1031284a5dbc2a7d4f6c8e7abdee9fad2af67b52e81426fe449c2d57947a2900","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1031284a5dbc2a7d4f6c8e7abdee9fad2af67b52e81426fe449c2d57947a2900","first_computed_at":"2026-06-11T01:09:26.732457Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-11T01:09:26.732457Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G4mRbjLx/we/3NBfN4ZFanW2Pz4zaADkbqpAo1V2KjikDTIlRutuhbWlQoo8d8vlJmGWgkagoR2wjvEStk/aBQ==","signature_status":"signed_v1","signed_at":"2026-06-11T01:09:26.733347Z","signed_message":"canonical_sha256_bytes"},"source_id":"2601.09072","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:713fa0d5fda93210750152776de37e430d9c051b5ce3ccdad3d8aaba026df250","sha256:c4ede73685b32a213726458a27ec1beb9db0d596b930bc2fdbf2ae2a5d92ddef"],"state_sha256":"3cfd5620f66c10e96889856faf3f344edb556fc72f8d2999da587517f8556f18"}