{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:QQEILSJR4O7IJFGWU5HFL3IRST","short_pith_number":"pith:QQEILSJR","schema_version":"1.0","canonical_sha256":"840885c931e3be8494d6a74e55ed1194fa692a747c820831313af0c217e67c45","source":{"kind":"arxiv","id":"2607.16675","version":1},"attestation_state":"computed","paper":{"title":"Isotonic Conformal Prediction","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.LG","stat.ME"],"primary_cat":"stat.ML","authors_text":"Archer Y. Yang, Daniel Bensimon, Eric D. Kolaczyk, Sean Xiang Yu","submitted_at":"2026-07-18T07:11:05Z","abstract_excerpt":"A point prediction that is well calibrated on average can still be systematically biased conditional on its own value, undermining its use in downstream decision-making. We consider two objectives for reliable uncertainty quantification: self-calibration, requiring a point prediction to be unbiased conditional on its own value, and prediction-conditional validity, requiring a prediction interval to attain nominal coverage conditional on the prediction. Self-Calibrating Conformal Prediction (SC-CP) attains both objectives exactly in finite samples, but requires refitting its calibrator for ever"},"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":"2607.16675","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"stat.ML","submitted_at":"2026-07-18T07:11:05Z","cross_cats_sorted":["cs.LG","stat.ME"],"title_canon_sha256":"3a139e2204a85d88e7f7ca3bd0e63b089f16afe4d3c4e8d60bb4228caadc4e22","abstract_canon_sha256":"f16ce98d569213091a5f11ca49cd5285edbe355bc8db809beb538943be7ca4bc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-21T01:20:21.404654Z","signature_b64":"JkYQt7RCKN8wZN06VgiFhaYnHqfQ7j4BatpYoM91k9rUwf0aVxxuaTj03cxkzF7dgzzdKI2ZXtysg1I9Uk4MAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"840885c931e3be8494d6a74e55ed1194fa692a747c820831313af0c217e67c45","last_reissued_at":"2026-07-21T01:20:21.403793Z","signature_status":"signed_v1","first_computed_at":"2026-07-21T01:20:21.403793Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Isotonic Conformal Prediction","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.LG","stat.ME"],"primary_cat":"stat.ML","authors_text":"Archer Y. Yang, Daniel Bensimon, Eric D. Kolaczyk, Sean Xiang Yu","submitted_at":"2026-07-18T07:11:05Z","abstract_excerpt":"A point prediction that is well calibrated on average can still be systematically biased conditional on its own value, undermining its use in downstream decision-making. We consider two objectives for reliable uncertainty quantification: self-calibration, requiring a point prediction to be unbiased conditional on its own value, and prediction-conditional validity, requiring a prediction interval to attain nominal coverage conditional on the prediction. Self-Calibrating Conformal Prediction (SC-CP) attains both objectives exactly in finite samples, but requires refitting its calibrator for ever"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.16675","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/2607.16675/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":"2607.16675","created_at":"2026-07-21T01:20:21.404218+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.16675v1","created_at":"2026-07-21T01:20:21.404218+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.16675","created_at":"2026-07-21T01:20:21.404218+00:00"},{"alias_kind":"pith_short_12","alias_value":"QQEILSJR4O7I","created_at":"2026-07-21T01:20:21.404218+00:00"},{"alias_kind":"pith_short_16","alias_value":"QQEILSJR4O7IJFGW","created_at":"2026-07-21T01:20:21.404218+00:00"},{"alias_kind":"pith_short_8","alias_value":"QQEILSJR","created_at":"2026-07-21T01:20:21.404218+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/QQEILSJR4O7IJFGWU5HFL3IRST","json":"https://pith.science/pith/QQEILSJR4O7IJFGWU5HFL3IRST.json","graph_json":"https://pith.science/api/pith-number/QQEILSJR4O7IJFGWU5HFL3IRST/graph.json","events_json":"https://pith.science/api/pith-number/QQEILSJR4O7IJFGWU5HFL3IRST/events.json","paper":"https://pith.science/paper/QQEILSJR"},"agent_actions":{"view_html":"https://pith.science/pith/QQEILSJR4O7IJFGWU5HFL3IRST","download_json":"https://pith.science/pith/QQEILSJR4O7IJFGWU5HFL3IRST.json","view_paper":"https://pith.science/paper/QQEILSJR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.16675&json=true","fetch_graph":"https://pith.science/api/pith-number/QQEILSJR4O7IJFGWU5HFL3IRST/graph.json","fetch_events":"https://pith.science/api/pith-number/QQEILSJR4O7IJFGWU5HFL3IRST/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QQEILSJR4O7IJFGWU5HFL3IRST/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QQEILSJR4O7IJFGWU5HFL3IRST/action/storage_attestation","attest_author":"https://pith.science/pith/QQEILSJR4O7IJFGWU5HFL3IRST/action/author_attestation","sign_citation":"https://pith.science/pith/QQEILSJR4O7IJFGWU5HFL3IRST/action/citation_signature","submit_replication":"https://pith.science/pith/QQEILSJR4O7IJFGWU5HFL3IRST/action/replication_record"}},"created_at":"2026-07-21T01:20:21.404218+00:00","updated_at":"2026-07-21T01:20:21.404218+00:00"}