{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:LA526ICRLRCGJHXYUUPFGJMFPQ","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":"83aaa61398800deaa3368cb0ddb5a182fd26324e672e679c34b2ec8fd7b6888b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-15T23:37:41Z","title_canon_sha256":"4963ecabaf1486cf4a136244a6e2e4260ecb213565f6125f9ee6875ca658c6d0"},"schema_version":"1.0","source":{"id":"1911.06915","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.06915","created_at":"2026-07-05T00:19:40Z"},{"alias_kind":"arxiv_version","alias_value":"1911.06915v1","created_at":"2026-07-05T00:19:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.06915","created_at":"2026-07-05T00:19:40Z"},{"alias_kind":"pith_short_12","alias_value":"LA526ICRLRCG","created_at":"2026-07-05T00:19:40Z"},{"alias_kind":"pith_short_16","alias_value":"LA526ICRLRCGJHXY","created_at":"2026-07-05T00:19:40Z"},{"alias_kind":"pith_short_8","alias_value":"LA526ICR","created_at":"2026-07-05T00:19:40Z"}],"graph_snapshots":[{"event_id":"sha256:040cdd8479fa513a11f75cefea12874d5be591a2d6aa970ec6ee8e4e824c9d71","target":"graph","created_at":"2026-07-05T00:19:40Z","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/1911.06915/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automated classification of chief complaints from patient-generated text is a critical first step in developing scalable platforms to triage patients without human intervention. In this work, we evaluate several approaches to chief complaint classification using a novel Chief Complaint (CC) Dataset that contains ~200,000 patient-generated reasons-for-visit entries mapped to a set of 795 discrete chief complaints. We examine the use of several fine-tuned bidirectional transformer (BERT) models trained on both unrelated texts as well as on the CC dataset. We contrast this performance with a TF-I","authors_text":"Caleb Goodwin, Daniel S. Zisook, Ian M. Finn, Ilya Valmianski, Naqi Khan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-15T23:37:41Z","title":"Evaluating robustness of language models for chief complaint extraction from patient-generated text"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.06915","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":"sha256:395c2a7ec0d54338746a3d4ee96fe97ff43b30b3f1c864bb621fecf0ef825e64","target":"record","created_at":"2026-07-05T00:19:40Z","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":"83aaa61398800deaa3368cb0ddb5a182fd26324e672e679c34b2ec8fd7b6888b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-15T23:37:41Z","title_canon_sha256":"4963ecabaf1486cf4a136244a6e2e4260ecb213565f6125f9ee6875ca658c6d0"},"schema_version":"1.0","source":{"id":"1911.06915","kind":"arxiv","version":1}},"canonical_sha256":"583baf20515c44649ef8a51e5325857c081a8f1dfb42859852bd11015f0a2594","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"583baf20515c44649ef8a51e5325857c081a8f1dfb42859852bd11015f0a2594","first_computed_at":"2026-07-05T00:19:40.657176Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:19:40.657176Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3Df5HNCcBermgIf3BG7lDnvI9fZdKvnZvx0rIGZq3l+RPEiNK+7pl2aA3D6O1houU28BpTZ4nUeXQmmAdUs0Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:19:40.657744Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.06915","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:395c2a7ec0d54338746a3d4ee96fe97ff43b30b3f1c864bb621fecf0ef825e64","sha256:040cdd8479fa513a11f75cefea12874d5be591a2d6aa970ec6ee8e4e824c9d71"],"state_sha256":"838ce96d514e48b971fec71bf8e6860dce91536990bc60f933ff33ebede9dc8c"}