{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:RCRO26JTYW5KKJX3JQRVRUVPVQ","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":"a00b3f88bc5428d2063a26bb858451ca34440c832ce4919778f713437490122f","cross_cats_sorted":["stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2023-12-20T17:45:20Z","title_canon_sha256":"6d92146cc32d5097f353fab4f91f5723c5fcbcab913f5c61fd20e21e3c391adc"},"schema_version":"1.0","source":{"id":"2312.13331","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.13331","created_at":"2026-07-05T07:26:43Z"},{"alias_kind":"arxiv_version","alias_value":"2312.13331v1","created_at":"2026-07-05T07:26:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.13331","created_at":"2026-07-05T07:26:43Z"},{"alias_kind":"pith_short_12","alias_value":"RCRO26JTYW5K","created_at":"2026-07-05T07:26:43Z"},{"alias_kind":"pith_short_16","alias_value":"RCRO26JTYW5KKJX3","created_at":"2026-07-05T07:26:43Z"},{"alias_kind":"pith_short_8","alias_value":"RCRO26JT","created_at":"2026-07-05T07:26:43Z"}],"graph_snapshots":[{"event_id":"sha256:9a01c882f18ed089dfddd6cc1644b6e040e65b67661e51e0293e8b8a3904e2c7","target":"graph","created_at":"2026-07-05T07:26:43Z","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/2312.13331/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Monitoring small-area geographical population trends in opioid mortality has large scale implications to informing preventative resource allocation. A common approach to obtain small area estimates of opioid mortality is to use a standard disease mapping approach in which population-at-risk estimates are treated as fixed and known. Assuming fixed populations ignores the uncertainty surrounding small area population estimates, which may bias risk estimates and under-estimate their associated uncertainties. We present a Bayesian Spatial Berkson Error (BSBE) model to incorporate population-at-ris","authors_text":"Brent A. Coull, Emily N Peterson, Frederic B. Piel, Jarvis T. Chen, Lance A Waller, Loni P. Tabb, Rachel C. Nethery","cross_cats":["stat.AP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2023-12-20T17:45:20Z","title":"A Bayesian Spatial Berkson error approach to estimate small area opioid mortality rates accounting for population-at-risk uncertainty"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.13331","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":"sha256:7ba129db350746bc98bcf44706884b35861af718877836d6d2a050c0e6f9faa7","target":"record","created_at":"2026-07-05T07:26:43Z","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":"a00b3f88bc5428d2063a26bb858451ca34440c832ce4919778f713437490122f","cross_cats_sorted":["stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2023-12-20T17:45:20Z","title_canon_sha256":"6d92146cc32d5097f353fab4f91f5723c5fcbcab913f5c61fd20e21e3c391adc"},"schema_version":"1.0","source":{"id":"2312.13331","kind":"arxiv","version":1}},"canonical_sha256":"88a2ed7933c5baa526fb4c2358d2afac3617dd5b22baff1321bafed6adac358c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"88a2ed7933c5baa526fb4c2358d2afac3617dd5b22baff1321bafed6adac358c","first_computed_at":"2026-07-05T07:26:43.478548Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:26:43.478548Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QFPx6xJVDAaw6tf3Td7Sj2wDP2J1nsvnztkSECZK3dVGcpGFqH8FExWPsKybMHVQvOzW9WhLXwJgx9rKcUBPBA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:26:43.478977Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.13331","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7ba129db350746bc98bcf44706884b35861af718877836d6d2a050c0e6f9faa7","sha256:9a01c882f18ed089dfddd6cc1644b6e040e65b67661e51e0293e8b8a3904e2c7"],"state_sha256":"a66c04d12a3bdec8a91940e1ccd9e8d27a76e4308a030924abe79b1dc12b2c12"}