{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:O2G3J2F6FUBYHNZTUKEEIVS6QW","short_pith_number":"pith:O2G3J2F6","schema_version":"1.0","canonical_sha256":"768db4e8be2d0383b733a28844565e8583a2abccdbbf68633a41920af7daeedd","source":{"kind":"arxiv","id":"1307.3495","version":3},"attestation_state":"computed","paper":{"title":"False discovery rate regression: an application to neural synchrony detection in primary visual cortex","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"James G. Scott, Matthew A. Smith, Pengcheng Zhou, Robert E. Kass, Ryan C. Kelly","submitted_at":"2013-07-12T15:55:33Z","abstract_excerpt":"Many approaches for multiple testing begin with the assumption that all tests in a given study should be combined into a global false-discovery-rate analysis. But this may be inappropriate for many of today's large-scale screening problems, where auxiliary information about each test is often available, and where a combined analysis can lead to poorly calibrated error rates within different subsets of the experiment. To address this issue, we introduce an approach called false-discovery-rate regression that directly uses this auxiliary information to inform the outcome of each test. The method"},"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":"1307.3495","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-07-12T15:55:33Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"0a0c1fcbbd8907488f10e3afc2dbbc696372ed2807efa2666d9dbc45b1f0aa59","abstract_canon_sha256":"445d855c2721c35cfa83cdaa2a3ed3884a953bc88b43b6679362e1c5cfaf9f18"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:50:13.440213Z","signature_b64":"Yq8XDFgGT/IQV1h6kNKTfR8T03BfSvAUNclo22Bz1b3ifvoVl1waKkxHaEJquJ6U0c59kMKknKl+iUz/c6MlDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"768db4e8be2d0383b733a28844565e8583a2abccdbbf68633a41920af7daeedd","last_reissued_at":"2026-05-18T02:50:13.439723Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:50:13.439723Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"False discovery rate regression: an application to neural synchrony detection in primary visual cortex","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"James G. Scott, Matthew A. Smith, Pengcheng Zhou, Robert E. Kass, Ryan C. Kelly","submitted_at":"2013-07-12T15:55:33Z","abstract_excerpt":"Many approaches for multiple testing begin with the assumption that all tests in a given study should be combined into a global false-discovery-rate analysis. But this may be inappropriate for many of today's large-scale screening problems, where auxiliary information about each test is often available, and where a combined analysis can lead to poorly calibrated error rates within different subsets of the experiment. To address this issue, we introduce an approach called false-discovery-rate regression that directly uses this auxiliary information to inform the outcome of each test. The method"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1307.3495","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"1307.3495","created_at":"2026-05-18T02:50:13.439798+00:00"},{"alias_kind":"arxiv_version","alias_value":"1307.3495v3","created_at":"2026-05-18T02:50:13.439798+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1307.3495","created_at":"2026-05-18T02:50:13.439798+00:00"},{"alias_kind":"pith_short_12","alias_value":"O2G3J2F6FUBY","created_at":"2026-05-18T12:27:54.935989+00:00"},{"alias_kind":"pith_short_16","alias_value":"O2G3J2F6FUBYHNZT","created_at":"2026-05-18T12:27:54.935989+00:00"},{"alias_kind":"pith_short_8","alias_value":"O2G3J2F6","created_at":"2026-05-18T12:27:54.935989+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/O2G3J2F6FUBYHNZTUKEEIVS6QW","json":"https://pith.science/pith/O2G3J2F6FUBYHNZTUKEEIVS6QW.json","graph_json":"https://pith.science/api/pith-number/O2G3J2F6FUBYHNZTUKEEIVS6QW/graph.json","events_json":"https://pith.science/api/pith-number/O2G3J2F6FUBYHNZTUKEEIVS6QW/events.json","paper":"https://pith.science/paper/O2G3J2F6"},"agent_actions":{"view_html":"https://pith.science/pith/O2G3J2F6FUBYHNZTUKEEIVS6QW","download_json":"https://pith.science/pith/O2G3J2F6FUBYHNZTUKEEIVS6QW.json","view_paper":"https://pith.science/paper/O2G3J2F6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1307.3495&json=true","fetch_graph":"https://pith.science/api/pith-number/O2G3J2F6FUBYHNZTUKEEIVS6QW/graph.json","fetch_events":"https://pith.science/api/pith-number/O2G3J2F6FUBYHNZTUKEEIVS6QW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/O2G3J2F6FUBYHNZTUKEEIVS6QW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/O2G3J2F6FUBYHNZTUKEEIVS6QW/action/storage_attestation","attest_author":"https://pith.science/pith/O2G3J2F6FUBYHNZTUKEEIVS6QW/action/author_attestation","sign_citation":"https://pith.science/pith/O2G3J2F6FUBYHNZTUKEEIVS6QW/action/citation_signature","submit_replication":"https://pith.science/pith/O2G3J2F6FUBYHNZTUKEEIVS6QW/action/replication_record"}},"created_at":"2026-05-18T02:50:13.439798+00:00","updated_at":"2026-05-18T02:50:13.439798+00:00"}