{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:IWDWTOCPYO6GEMBVYHNUHS2TGM","short_pith_number":"pith:IWDWTOCP","schema_version":"1.0","canonical_sha256":"458769b84fc3bc623035c1db43cb533324b519f267de277392ad74a1c89e4815","source":{"kind":"arxiv","id":"2302.14011","version":2},"attestation_state":"computed","paper":{"title":"Causal isotonic calibration for heterogeneous treatment effects","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","stat.ME"],"primary_cat":"stat.ML","authors_text":"Alex Luedtke, Ernesto Ulloa-P\\'erez, Lars van der Laan, Marco Carone","submitted_at":"2023-02-27T18:07:49Z","abstract_excerpt":"We propose causal isotonic calibration, a novel nonparametric method for calibrating predictors of heterogeneous treatment effects. Furthermore, we introduce cross-calibration, a data-efficient variant of calibration that eliminates the need for hold-out calibration sets. Cross-calibration leverages cross-fitted predictors and generates a single calibrated predictor using all available data. Under weak conditions that do not assume monotonicity, we establish that both causal isotonic calibration and cross-calibration achieve fast doubly-robust calibration rates, as long as either the propensit"},"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":"2302.14011","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2023-02-27T18:07:49Z","cross_cats_sorted":["cs.LG","stat.ME"],"title_canon_sha256":"41dd7e3a3ae6ff1a701b37e97c9c1e44e3937a072d14fec66d822275fcbf9cee","abstract_canon_sha256":"f09a944bd988cb8f91cdbd07454ab0d57be92f934c580510e247cd3cebd5a503"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:17:46.995145Z","signature_b64":"T/4ktpaPNg2Q772kcUd1f56ce2LmG2Z57Fj8ODQ1P2WetaYoBD7Ce1GANRh6fTljw7RHQbADqjcP5Vjb/93nAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"458769b84fc3bc623035c1db43cb533324b519f267de277392ad74a1c89e4815","last_reissued_at":"2026-07-05T06:17:46.994722Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:17:46.994722Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Causal isotonic calibration for heterogeneous treatment effects","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","stat.ME"],"primary_cat":"stat.ML","authors_text":"Alex Luedtke, Ernesto Ulloa-P\\'erez, Lars van der Laan, Marco Carone","submitted_at":"2023-02-27T18:07:49Z","abstract_excerpt":"We propose causal isotonic calibration, a novel nonparametric method for calibrating predictors of heterogeneous treatment effects. Furthermore, we introduce cross-calibration, a data-efficient variant of calibration that eliminates the need for hold-out calibration sets. Cross-calibration leverages cross-fitted predictors and generates a single calibrated predictor using all available data. Under weak conditions that do not assume monotonicity, we establish that both causal isotonic calibration and cross-calibration achieve fast doubly-robust calibration rates, as long as either the propensit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.14011","kind":"arxiv","version":2},"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/2302.14011/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":"2302.14011","created_at":"2026-07-05T06:17:46.994793+00:00"},{"alias_kind":"arxiv_version","alias_value":"2302.14011v2","created_at":"2026-07-05T06:17:46.994793+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.14011","created_at":"2026-07-05T06:17:46.994793+00:00"},{"alias_kind":"pith_short_12","alias_value":"IWDWTOCPYO6G","created_at":"2026-07-05T06:17:46.994793+00:00"},{"alias_kind":"pith_short_16","alias_value":"IWDWTOCPYO6GEMBV","created_at":"2026-07-05T06:17:46.994793+00:00"},{"alias_kind":"pith_short_8","alias_value":"IWDWTOCP","created_at":"2026-07-05T06:17:46.994793+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2607.16675","citing_title":"Isotonic Conformal Prediction","ref_index":14,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/IWDWTOCPYO6GEMBVYHNUHS2TGM","json":"https://pith.science/pith/IWDWTOCPYO6GEMBVYHNUHS2TGM.json","graph_json":"https://pith.science/api/pith-number/IWDWTOCPYO6GEMBVYHNUHS2TGM/graph.json","events_json":"https://pith.science/api/pith-number/IWDWTOCPYO6GEMBVYHNUHS2TGM/events.json","paper":"https://pith.science/paper/IWDWTOCP"},"agent_actions":{"view_html":"https://pith.science/pith/IWDWTOCPYO6GEMBVYHNUHS2TGM","download_json":"https://pith.science/pith/IWDWTOCPYO6GEMBVYHNUHS2TGM.json","view_paper":"https://pith.science/paper/IWDWTOCP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2302.14011&json=true","fetch_graph":"https://pith.science/api/pith-number/IWDWTOCPYO6GEMBVYHNUHS2TGM/graph.json","fetch_events":"https://pith.science/api/pith-number/IWDWTOCPYO6GEMBVYHNUHS2TGM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IWDWTOCPYO6GEMBVYHNUHS2TGM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IWDWTOCPYO6GEMBVYHNUHS2TGM/action/storage_attestation","attest_author":"https://pith.science/pith/IWDWTOCPYO6GEMBVYHNUHS2TGM/action/author_attestation","sign_citation":"https://pith.science/pith/IWDWTOCPYO6GEMBVYHNUHS2TGM/action/citation_signature","submit_replication":"https://pith.science/pith/IWDWTOCPYO6GEMBVYHNUHS2TGM/action/replication_record"}},"created_at":"2026-07-05T06:17:46.994793+00:00","updated_at":"2026-07-05T06:17:46.994793+00:00"}