{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:PAB2CD75SQHQFGOYOOP5TB7ASF","short_pith_number":"pith:PAB2CD75","schema_version":"1.0","canonical_sha256":"7803a10ffd940f0299d8739fd987e091623b6472a6384968f8ebd96b8da95b93","source":{"kind":"arxiv","id":"2607.29064","version":1},"attestation_state":"computed","paper":{"title":"Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Rajendra K C Khatri, Sudhir Bharati, Sudip Bharati","submitted_at":"2026-07-31T06:32:02Z","abstract_excerpt":"Police crash narratives contain information that may supplement structured crash databases, but manual review is labor-intensive and it remains unclear how well large language models (LLMs) reproduce official crash coding. This study benchmarked six frontier LLMs by comparing narrative-derived crash attribute codes with corresponding fields in the Arkansas fatal-crash database. The analysis linked 5,587 fatal-crash narratives with 5,889 structured crash records from Arkansas (2015-2025), yielding 4,194 matched crashes. Six LLMs were evaluated using an identical zero-shot prompt to code crash m"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2607.29064","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-31T06:32:02Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"579ac1d7ecf812e6ae6ec98a25505aaaec45381ee1591247cf74d6c66cd5a49d","abstract_canon_sha256":"5d331628196d757a0845c45fe881b6ceb4bf4a60194a9901ae81fd1fbb51bc62"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-03T01:18:13.268071Z","signature_b64":"j/RgLfgie6xb36rrmf1skl3aQHdL1ONLAvQwMD1OwT7+v0j4q9Xnq4e6bOqHzcKBnK3akdftCoy6rFjn5Z0tBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7803a10ffd940f0299d8739fd987e091623b6472a6384968f8ebd96b8da95b93","last_reissued_at":"2026-08-03T01:18:13.266500Z","signature_status":"signed_v1","first_computed_at":"2026-08-03T01:18:13.266500Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Rajendra K C Khatri, Sudhir Bharati, Sudip Bharati","submitted_at":"2026-07-31T06:32:02Z","abstract_excerpt":"Police crash narratives contain information that may supplement structured crash databases, but manual review is labor-intensive and it remains unclear how well large language models (LLMs) reproduce official crash coding. This study benchmarked six frontier LLMs by comparing narrative-derived crash attribute codes with corresponding fields in the Arkansas fatal-crash database. The analysis linked 5,587 fatal-crash narratives with 5,889 structured crash records from Arkansas (2015-2025), yielding 4,194 matched crashes. Six LLMs were evaluated using an identical zero-shot prompt to code crash m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.29064","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/2607.29064/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.29064","created_at":"2026-08-03T01:18:13.267437+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.29064v1","created_at":"2026-08-03T01:18:13.267437+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.29064","created_at":"2026-08-03T01:18:13.267437+00:00"},{"alias_kind":"pith_short_12","alias_value":"PAB2CD75SQHQ","created_at":"2026-08-03T01:18:13.267437+00:00"},{"alias_kind":"pith_short_16","alias_value":"PAB2CD75SQHQFGOY","created_at":"2026-08-03T01:18:13.267437+00:00"},{"alias_kind":"pith_short_8","alias_value":"PAB2CD75","created_at":"2026-08-03T01:18:13.267437+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PAB2CD75SQHQFGOYOOP5TB7ASF","json":"https://pith.science/pith/PAB2CD75SQHQFGOYOOP5TB7ASF.json","graph_json":"https://pith.science/api/pith-number/PAB2CD75SQHQFGOYOOP5TB7ASF/graph.json","events_json":"https://pith.science/api/pith-number/PAB2CD75SQHQFGOYOOP5TB7ASF/events.json","paper":"https://pith.science/paper/PAB2CD75"},"agent_actions":{"view_html":"https://pith.science/pith/PAB2CD75SQHQFGOYOOP5TB7ASF","download_json":"https://pith.science/pith/PAB2CD75SQHQFGOYOOP5TB7ASF.json","view_paper":"https://pith.science/paper/PAB2CD75","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.29064&json=true","fetch_graph":"https://pith.science/api/pith-number/PAB2CD75SQHQFGOYOOP5TB7ASF/graph.json","fetch_events":"https://pith.science/api/pith-number/PAB2CD75SQHQFGOYOOP5TB7ASF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PAB2CD75SQHQFGOYOOP5TB7ASF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PAB2CD75SQHQFGOYOOP5TB7ASF/action/storage_attestation","attest_author":"https://pith.science/pith/PAB2CD75SQHQFGOYOOP5TB7ASF/action/author_attestation","sign_citation":"https://pith.science/pith/PAB2CD75SQHQFGOYOOP5TB7ASF/action/citation_signature","submit_replication":"https://pith.science/pith/PAB2CD75SQHQFGOYOOP5TB7ASF/action/replication_record"}},"created_at":"2026-08-03T01:18:13.267437+00:00","updated_at":"2026-08-03T01:18:13.267437+00:00"}