{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:6GVDWK3WRO62WS3LGG2XBMJ6KW","merge_version":"pith-open-graph-merge-v1","event_count":4,"valid_event_count":4,"invalid_event_count":0,"equivocation_count":1,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"2fc59e567fa7ea0323826d1f5510584b40cef919195e8b3397fc5b306c5eedc2","cross_cats_sorted":["econ.EM","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.AP","submitted_at":"2026-05-15T19:56:25Z","title_canon_sha256":"9d8202e1ef0143570d4f4243523ccb3dee40c4ee199b6da86164e5cb6119d01e"},"schema_version":"1.0","source":{"id":"2605.16593","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.16593","created_at":"2026-05-20T00:02:31Z"},{"alias_kind":"arxiv_version","alias_value":"2605.16593v1","created_at":"2026-05-20T00:02:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.16593","created_at":"2026-05-20T00:02:31Z"},{"alias_kind":"pith_short_12","alias_value":"6GVDWK3WRO62","created_at":"2026-05-20T00:02:31Z"},{"alias_kind":"pith_short_16","alias_value":"6GVDWK3WRO62WS3L","created_at":"2026-05-20T00:02:31Z"},{"alias_kind":"pith_short_8","alias_value":"6GVDWK3W","created_at":"2026-05-20T00:02:31Z"}],"graph_snapshots":[{"event_id":"sha256:d4553520ee294a41d882d82ef142a42bf13e80d67a966660ce20b08755bba658","target":"graph","created_at":"2026-05-20T00:02:31Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"Reallocating treatments among treated individuals could have reduced total treatment costs by CAN$3.6-4.9 million while still increasing aggregate health benefits relative to the status quo."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"The outcome model is correctly specified within each homogeneous subgroup identified by the weighted K-means algorithm (abstract, paragraph on CATE estimation)."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"A weighted K-means plus decision-tree pipeline learns multi-action policies from observational data and is applied to HCV treatment choices for HIV co-infected patients, finding a high-clearance subgroup and potential cost savings of CAN$3.6-4.9 million."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"Reallocating hepatitis C treatments among HIV co-infected patients could cut costs by CAN$3.6-4.9 million while increasing health benefits."}],"snapshot_sha256":"3477237fc7f50412ef7dabc5161085c927744190af1b67957270f85e316df238"},"formal_canon":{"evidence_count":2,"snapshot_sha256":"2f056e1a012813972fe2f4ca2f50b6362bacd9f97a3f46f1dbc84d5741e74e3c"},"integrity":{"available":true,"clean":false,"detectors_run":[{"findings_count":2,"name":"doi_compliance","ran_at":"2026-05-19T21:02:49.991609Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"doi_title_agreement","ran_at":"2026-05-19T21:01:19.338282Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T19:21:56.829815Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T18:33:26.605879Z","status":"skipped","version":"1.0.0"}],"endpoint":"/pith/2605.16593/integrity.json","findings":[{"audited_at":"2026-05-19T21:02:49.991609Z","detected_arxiv_id":null,"detected_doi":"10.3982/qe517","detector":"doi_compliance","finding_type":"broken_identifier","note":"DOI '10.3982/qe517' as printed in the bibliography is syntactically invalid and cannot resolve.","ref_index":53,"severity":"critical","verdict_class":"incontrovertible"},{"audited_at":"2026-05-19T21:02:49.991609Z","detected_arxiv_id":null,"detected_doi":"10.3982/qe170","detector":"doi_compliance","finding_type":"broken_identifier","note":"DOI '10.3982/qe170' as printed in the bibliography is syntactically invalid and cannot resolve.","ref_index":184,"severity":"critical","verdict_class":"incontrovertible"}],"snapshot_sha256":"566d4f853a60887f681a0407ab695372384fb24bda03975d0791ee8c69302b98","summary":{"advisory":0,"by_detector":{"doi_compliance":{"advisory":0,"critical":2,"informational":0,"total":2}},"critical":2,"informational":0}},"paper":{"abstract_excerpt":"Decision-makers frequently must choose a single action from a finite set of alternatives -- for example, physicians selecting a treatment, investors choosing a portfolio risk level, or judges determining sentences. To improve outcomes, policymakers often issue policy rules or guidelines to inform such choices. In this paper, I show how to generally derive policy rules from observational data in a multi-action framework under relatively weak assumptions about the underlying structure of the heterogeneous sampled population. Conditional average treatment effects (CATEs) are consistently estimate","authors_text":"Rapha\\\"el Langevin","cross_cats":["econ.EM","stat.ML"],"headline":"Reallocating hepatitis C treatments among HIV co-infected patients could cut costs by CAN$3.6-4.9 million while increasing health benefits.","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.AP","submitted_at":"2026-05-15T19:56:25Z","title":"Policy Learning with Observational Data: The Case of Hepatitis C Treatment for HIV/HCV Co-Infected Patients"},"references":{"count":299,"internal_anchors":0,"resolved_work":299,"sample":[{"cited_arxiv_id":"","doi":"10.1186/s40545-021-00385-w","is_internal_anchor":false,"ref_index":1,"title":"Journal of Pharmaceutical Policy and Practice , author =","work_id":"5204c464-226a-4308-9571-45e45decdc21","year":2021},{"cited_arxiv_id":"","doi":"10.1002/hec.1214","is_internal_anchor":false,"ref_index":2,"title":"Health Economics , author =","work_id":"404af2d7-952f-4ea8-8b88-4cdb53a2c68e","year":2007},{"cited_arxiv_id":"","doi":"10.48550/arxiv.2601.20197","is_internal_anchor":false,"ref_index":3,"title":"Langevin, Raphaël , month = feb, year =. Bias-. doi:10.48550/arXiv.2601.20197 , abstract =","work_id":"4562dc6c-4b4f-40ed-9d15-8f3ba5e4b342","year":null},{"cited_arxiv_id":"","doi":"10.18553/jmcp.2020.26.7.879","is_internal_anchor":false,"ref_index":4,"title":"Journal of Managed Care & Specialty Pharmacy , author =","work_id":"bf91949c-eb10-41c9-abe9-f026e4e081db","year":2020},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"title":"Tibshirani, Julie and Athey, Susan and Sverdrup, Erik and Wager, Stefan , month = nov, year =. Generalized","work_id":"d7061ede-24e3-48e7-ba99-2e9b9195af7f","year":null}],"snapshot_sha256":"689edf88f4f331384b2273145e5649b4ac936c9af1006491530ec1cb3799ab10"},"source":{"id":"2605.16593","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-19T20:53:17.716712Z","id":"561e1ec5-7422-4028-8d70-9578f89f4b35","model_set":{"reader":"grok-4.3"},"one_line_summary":"A weighted K-means plus decision-tree pipeline learns multi-action policies from observational data and is applied to HCV treatment choices for HIV co-infected patients, finding a high-clearance subgroup and potential cost savings of CAN$3.6-4.9 million.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Reallocating hepatitis C treatments among HIV co-infected patients could cut costs by CAN$3.6-4.9 million while increasing health benefits.","strongest_claim":"Reallocating treatments among treated individuals could have reduced total treatment costs by CAN$3.6-4.9 million while still increasing aggregate health benefits relative to the status quo.","weakest_assumption":"The outcome model is correctly specified within each homogeneous subgroup identified by the weighted K-means algorithm (abstract, paragraph on CATE estimation)."}},"verdict_id":"561e1ec5-7422-4028-8d70-9578f89f4b35"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:f16c0fe50da7f506c51d7880818ded3cd74921111565e709fc7f2816f9f18a57","target":"record","created_at":"2026-05-20T00:02:31Z","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":"2fc59e567fa7ea0323826d1f5510584b40cef919195e8b3397fc5b306c5eedc2","cross_cats_sorted":["econ.EM","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.AP","submitted_at":"2026-05-15T19:56:25Z","title_canon_sha256":"9d8202e1ef0143570d4f4243523ccb3dee40c4ee199b6da86164e5cb6119d01e"},"schema_version":"1.0","source":{"id":"2605.16593","kind":"arxiv","version":1}},"canonical_sha256":"f1aa3b2b768bbdab4b6b31b570b13e55a481c6b98be2a295722a29625b9d9774","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f1aa3b2b768bbdab4b6b31b570b13e55a481c6b98be2a295722a29625b9d9774","first_computed_at":"2026-05-20T00:02:31.590858Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:02:31.590858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ikGxmvyXSAOWlJVVu8ofSwy69ADSrjyS3K10aIEwoFQJJvK6fzkHVf63py3M9xZ0ggW7wdNIM8QL8CRoHE09CQ==","signature_status":"signed_v1","signed_at":"2026-05-20T00:02:31.591823Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.16593","source_kind":"arxiv","source_version":1}}},"equivocations":[{"signer_id":"pith.science","event_type":"integrity_finding","target":"integrity","event_ids":["sha256:9255f41af8c89df7eb3e4ab66c73621e0ebef1e3d956698dffde2830c21e91e5","sha256:c7d47b626e0d93fab3ebc78a5fa0ecfc628c5c6d0b65c8bb3d94305a43c2ab6f"]}],"invalid_events":[],"applied_event_ids":["sha256:f16c0fe50da7f506c51d7880818ded3cd74921111565e709fc7f2816f9f18a57","sha256:d4553520ee294a41d882d82ef142a42bf13e80d67a966660ce20b08755bba658"],"state_sha256":"353aa94d479f78f13856826ab253ed4600cc7572e76c1ceede0b95a4bf5503d5"}