{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:MV4A4ZGMWLB3BJW3AIHBVIFZIB","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":"8aa35b6b23b008d877e469a8d8810addc9d57ca1029fef8a2abbe2f6cebc3bed","cross_cats_sorted":["cs.AI","math.ST","stat.ML","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2019-10-23T13:44:38Z","title_canon_sha256":"af89fc0b1a048c627b07520933e2958410b5cebe2ad9ac1b4e97def9e873cc74"},"schema_version":"1.0","source":{"id":"1910.10562","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.10562","created_at":"2026-07-05T04:21:25Z"},{"alias_kind":"arxiv_version","alias_value":"1910.10562v4","created_at":"2026-07-05T04:21:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.10562","created_at":"2026-07-05T04:21:25Z"},{"alias_kind":"pith_short_12","alias_value":"MV4A4ZGMWLB3","created_at":"2026-07-05T04:21:25Z"},{"alias_kind":"pith_short_16","alias_value":"MV4A4ZGMWLB3BJW3","created_at":"2026-07-05T04:21:25Z"},{"alias_kind":"pith_short_8","alias_value":"MV4A4ZGM","created_at":"2026-07-05T04:21:25Z"}],"graph_snapshots":[{"event_id":"sha256:f716030904ea0f325413bafd8a0052099e3d715c945811db3240f55df2115692","target":"graph","created_at":"2026-07-05T04:21:25Z","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/1910.10562/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Conformal prediction is a popular tool for providing valid prediction sets for classification and regression problems, without relying on any distributional assumptions on the data. While the traditional description of conformal prediction starts with a nonconformity score, we provide an alternate (but equivalent) view that starts with a sequence of nested sets and calibrates them to find a valid prediction set. The nested framework subsumes all nonconformity scores, including recent proposals based on quantile regression and density estimation. While these ideas were originally derived based ","authors_text":"Aaditya K. Ramdas, Arun K. Kuchibhotla, Chirag Gupta","cross_cats":["cs.AI","math.ST","stat.ML","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2019-10-23T13:44:38Z","title":"Nested conformal prediction and quantile out-of-bag ensemble methods"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.10562","kind":"arxiv","version":4},"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":"sha256:3fe271f6c696e0f2a6ddb06abe1e2d245ef0ba2af476962a49fd247450768fb0","target":"record","created_at":"2026-07-05T04:21:25Z","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":"8aa35b6b23b008d877e469a8d8810addc9d57ca1029fef8a2abbe2f6cebc3bed","cross_cats_sorted":["cs.AI","math.ST","stat.ML","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2019-10-23T13:44:38Z","title_canon_sha256":"af89fc0b1a048c627b07520933e2958410b5cebe2ad9ac1b4e97def9e873cc74"},"schema_version":"1.0","source":{"id":"1910.10562","kind":"arxiv","version":4}},"canonical_sha256":"65780e64ccb2c3b0a6db020e1aa0b94051c2517219e13b17f5f010dea39230c6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"65780e64ccb2c3b0a6db020e1aa0b94051c2517219e13b17f5f010dea39230c6","first_computed_at":"2026-07-05T04:21:25.504864Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:21:25.504864Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WJkGOY+L2KOlGqnj2n7220cZrZKoWTtGPKWnbWMbaB0esWvUDa00R60iqx68sjZB4oL9fv4v3LRYx+mf60ZvCA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:21:25.505276Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.10562","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3fe271f6c696e0f2a6ddb06abe1e2d245ef0ba2af476962a49fd247450768fb0","sha256:f716030904ea0f325413bafd8a0052099e3d715c945811db3240f55df2115692"],"state_sha256":"d7036cc7e04f0f3b2cd970081fc7c37417ab545739cee28615743ce14913e9a9"}