{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:GOCKFHJLS6QGCXUNLOV6RK7FUT","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":"f4ec1dc2dbd54dcbbb11496fd507ea552b882cb6cb77082da5f75ffaae6b7a29","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2023-03-01T02:30:11Z","title_canon_sha256":"6737a8d25f80f19a3f251f7abe265ab60bf5be119fd0fc258c5db692cc54de04"},"schema_version":"1.0","source":{"id":"2303.01229","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.01229","created_at":"2026-07-05T06:16:16Z"},{"alias_kind":"arxiv_version","alias_value":"2303.01229v2","created_at":"2026-07-05T06:16:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.01229","created_at":"2026-07-05T06:16:16Z"},{"alias_kind":"pith_short_12","alias_value":"GOCKFHJLS6QG","created_at":"2026-07-05T06:16:16Z"},{"alias_kind":"pith_short_16","alias_value":"GOCKFHJLS6QGCXUN","created_at":"2026-07-05T06:16:16Z"},{"alias_kind":"pith_short_8","alias_value":"GOCKFHJL","created_at":"2026-07-05T06:16:16Z"}],"graph_snapshots":[{"event_id":"sha256:957b0f73b9e150762ef8d46899b0b96a76321e96ef08d1f74ff91c75b6a4e44f","target":"graph","created_at":"2026-07-05T06:16:16Z","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/2303.01229/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large-language models have recently demonstrated impressive zero-shot capabilities in a variety of natural language tasks such as summarization, dialogue generation, and question-answering. Despite many promising applications in clinical medicine, adoption of these models in real-world settings has been largely limited by their tendency to generate incorrect and sometimes even toxic statements. In this study, we develop Almanac, a large language model framework augmented with retrieval capabilities for medical guideline and treatment recommendations. Performance on a novel dataset of clinical ","authors_text":"Akash Chaurasia, Alex R. Dalal, Curt Langlotz, Cyril Zakka, Euan Ashley, Jack Boyd, Jennifer L. Kim, Joanna Nelson, Karen Hirsch, Kathleen Boyd, Kevin Alexander, Michael Moor, Rohan Shad, William Hiesinger","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2023-03-01T02:30:11Z","title":"Almanac: Retrieval-Augmented Language Models for Clinical Medicine"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.01229","kind":"arxiv","version":2},"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":"sha256:46016aa0626243ac103ada3d67c026bed4ea6202e10b65aefeb2c06d2452e6b2","target":"record","created_at":"2026-07-05T06:16:16Z","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":"f4ec1dc2dbd54dcbbb11496fd507ea552b882cb6cb77082da5f75ffaae6b7a29","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2023-03-01T02:30:11Z","title_canon_sha256":"6737a8d25f80f19a3f251f7abe265ab60bf5be119fd0fc258c5db692cc54de04"},"schema_version":"1.0","source":{"id":"2303.01229","kind":"arxiv","version":2}},"canonical_sha256":"3384a29d2b97a0615e8d5babe8abe5a4efc6a55dbba135c1b850de90de102103","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3384a29d2b97a0615e8d5babe8abe5a4efc6a55dbba135c1b850de90de102103","first_computed_at":"2026-07-05T06:16:16.787583Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:16:16.787583Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1Wfzc160m3Mzewq+noquD90oy/65vvwmMUs+xtAABAFWvpzPCh6Okv5UkUMIS2piDlBxSrbi6lXEG64WISEOBw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:16:16.788103Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.01229","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:46016aa0626243ac103ada3d67c026bed4ea6202e10b65aefeb2c06d2452e6b2","sha256:957b0f73b9e150762ef8d46899b0b96a76321e96ef08d1f74ff91c75b6a4e44f"],"state_sha256":"7021f31a72e544cfc51c49f44fe306e2f7e1a1bc016a91c06a6d4be337cea008"}