{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:U3TQUPPAMBJSNQBBPAEKME5THJ","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":"c2cda105573141457186760e5c4f83f656e57e4a44a90e77f054defd9d66d62f","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2018-02-14T11:41:56Z","title_canon_sha256":"42f5a16652ba506599c9230812fa68c2a2371261ccba94b0d005f0b0d89ca3d5"},"schema_version":"1.0","source":{"id":"1802.05046","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.05046","created_at":"2026-05-18T00:20:35Z"},{"alias_kind":"arxiv_version","alias_value":"1802.05046v2","created_at":"2026-05-18T00:20:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.05046","created_at":"2026-05-18T00:20:35Z"},{"alias_kind":"pith_short_12","alias_value":"U3TQUPPAMBJS","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"U3TQUPPAMBJSNQBB","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"U3TQUPPA","created_at":"2026-05-18T12:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:4a5558728eda724a8eac7e7f5c19082e98dfa59ecb26f1e7911ebbb08153e14f","target":"graph","created_at":"2026-05-18T00:20:35Z","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"},"paper":{"abstract_excerpt":"Causal inference analysis is the estimation of the effects of actions on outcomes. In the context of healthcare data this means estimating the outcome of counter-factual treatments (i.e. including treatments that were not observed) on a patient's outcome. Compared to classic machine learning methods, evaluation and validation of causal inference analysis is more challenging because ground truth data of counter-factual outcome can never be obtained in any real-world scenario. Here, we present a comprehensive framework for benchmarking algorithms that estimate causal effect. The framework includ","authors_text":"Chen Yanover, Ehud Karavani, Yaara Goldschmnidt, Yishai Shimoni","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2018-02-14T11:41:56Z","title":"Benchmarking Framework for Performance-Evaluation of Causal Inference Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.05046","kind":"arxiv","version":2},"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":"sha256:6485084e174c24a83e46f98d8e0b68154d969262952fd957ed1216342e492180","target":"record","created_at":"2026-05-18T00:20:35Z","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":"c2cda105573141457186760e5c4f83f656e57e4a44a90e77f054defd9d66d62f","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2018-02-14T11:41:56Z","title_canon_sha256":"42f5a16652ba506599c9230812fa68c2a2371261ccba94b0d005f0b0d89ca3d5"},"schema_version":"1.0","source":{"id":"1802.05046","kind":"arxiv","version":2}},"canonical_sha256":"a6e70a3de0605326c0217808a613b33a6d4ab031fa3479ac6ac89514c1cac7e8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a6e70a3de0605326c0217808a613b33a6d4ab031fa3479ac6ac89514c1cac7e8","first_computed_at":"2026-05-18T00:20:35.096411Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:20:35.096411Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8NJfXo+hSSav39ctHs/fUj+GyGUqU2d7x1nkXXBkO6AetrexzAltZY631JvE467uU8F7NU75RR1JCQ5LXxg6Bg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:20:35.096906Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.05046","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6485084e174c24a83e46f98d8e0b68154d969262952fd957ed1216342e492180","sha256:4a5558728eda724a8eac7e7f5c19082e98dfa59ecb26f1e7911ebbb08153e14f"],"state_sha256":"742d9cb16325dbd4e6e480e1b2f48ce7b9b647af31eaf7fc07c738855fabee66"}