{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:HCFCD3FGM4QYIBO5USLXD6OALS","short_pith_number":"pith:HCFCD3FG","schema_version":"1.0","canonical_sha256":"388a21eca667218405dda49771f9c05cad04f607bd4b18fd21c5c2f36288058b","source":{"kind":"arxiv","id":"2306.10220","version":1},"attestation_state":"computed","paper":{"title":"Reevaluating the Role of Race and Ethnicity in Diabetes Screening","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"David Kent, Madison Coots, Sharad Goel, Soroush Saghafian","submitted_at":"2023-06-17T00:58:48Z","abstract_excerpt":"There is active debate over whether to consider patient race and ethnicity when estimating disease risk. By accounting for race and ethnicity, it is possible to improve the accuracy of risk predictions, but there is concern that their use may encourage a racialized view of medicine. In diabetes risk models, despite substantial gains in statistical accuracy from using race and ethnicity, the gains in clinical utility are surprisingly modest. These modest clinical gains stem from two empirical patterns: first, the vast majority of individuals receive the same screening recommendation regardless "},"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":"2306.10220","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.AP","submitted_at":"2023-06-17T00:58:48Z","cross_cats_sorted":[],"title_canon_sha256":"e405bdb557f98871762f7db73117715017ad9fa9f77c17624a2dd7e380ea7e09","abstract_canon_sha256":"c8620312cdb505970df132ccda46c1fda7e84d1f87928856fe391a44d63a3702"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:21:35.569942Z","signature_b64":"W4CgwrwRgw/9UwhmZPqGJPWWau06SGr6X/YW8N3WP3EqFn3+IztR4bt30KRsAP6lgZ8/D71ZebDeqDOLEu2DDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"388a21eca667218405dda49771f9c05cad04f607bd4b18fd21c5c2f36288058b","last_reissued_at":"2026-07-05T06:21:35.569518Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:21:35.569518Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Reevaluating the Role of Race and Ethnicity in Diabetes Screening","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"David Kent, Madison Coots, Sharad Goel, Soroush Saghafian","submitted_at":"2023-06-17T00:58:48Z","abstract_excerpt":"There is active debate over whether to consider patient race and ethnicity when estimating disease risk. By accounting for race and ethnicity, it is possible to improve the accuracy of risk predictions, but there is concern that their use may encourage a racialized view of medicine. In diabetes risk models, despite substantial gains in statistical accuracy from using race and ethnicity, the gains in clinical utility are surprisingly modest. These modest clinical gains stem from two empirical patterns: first, the vast majority of individuals receive the same screening recommendation regardless "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.10220","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/2306.10220/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":"2306.10220","created_at":"2026-07-05T06:21:35.569581+00:00"},{"alias_kind":"arxiv_version","alias_value":"2306.10220v1","created_at":"2026-07-05T06:21:35.569581+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.10220","created_at":"2026-07-05T06:21:35.569581+00:00"},{"alias_kind":"pith_short_12","alias_value":"HCFCD3FGM4QY","created_at":"2026-07-05T06:21:35.569581+00:00"},{"alias_kind":"pith_short_16","alias_value":"HCFCD3FGM4QYIBO5","created_at":"2026-07-05T06:21:35.569581+00:00"},{"alias_kind":"pith_short_8","alias_value":"HCFCD3FG","created_at":"2026-07-05T06:21:35.569581+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.21455","citing_title":"Mitigating Label Bias with Interpretable Rubric Embeddings","ref_index":48,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HCFCD3FGM4QYIBO5USLXD6OALS","json":"https://pith.science/pith/HCFCD3FGM4QYIBO5USLXD6OALS.json","graph_json":"https://pith.science/api/pith-number/HCFCD3FGM4QYIBO5USLXD6OALS/graph.json","events_json":"https://pith.science/api/pith-number/HCFCD3FGM4QYIBO5USLXD6OALS/events.json","paper":"https://pith.science/paper/HCFCD3FG"},"agent_actions":{"view_html":"https://pith.science/pith/HCFCD3FGM4QYIBO5USLXD6OALS","download_json":"https://pith.science/pith/HCFCD3FGM4QYIBO5USLXD6OALS.json","view_paper":"https://pith.science/paper/HCFCD3FG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2306.10220&json=true","fetch_graph":"https://pith.science/api/pith-number/HCFCD3FGM4QYIBO5USLXD6OALS/graph.json","fetch_events":"https://pith.science/api/pith-number/HCFCD3FGM4QYIBO5USLXD6OALS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HCFCD3FGM4QYIBO5USLXD6OALS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HCFCD3FGM4QYIBO5USLXD6OALS/action/storage_attestation","attest_author":"https://pith.science/pith/HCFCD3FGM4QYIBO5USLXD6OALS/action/author_attestation","sign_citation":"https://pith.science/pith/HCFCD3FGM4QYIBO5USLXD6OALS/action/citation_signature","submit_replication":"https://pith.science/pith/HCFCD3FGM4QYIBO5USLXD6OALS/action/replication_record"}},"created_at":"2026-07-05T06:21:35.569581+00:00","updated_at":"2026-07-05T06:21:35.569581+00:00"}