{"as_of":"2026-08-08T13:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:16d4a1bc7f83e23b521110f4014c9f7f623c549425c8222b7c3a6453a35042a3","coverage":[{"denominator":58,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":58,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:11:25.050455Z","state":"measured"},{"denominator":58,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":58,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.03347/citation-record","integrity":"/paper/2506.03347/integrity","json":"/paper/2506.03347/citation-record.json","paper":"/paper/2506.03347"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.423138Z","title":"On the Use of Covariate Supersets for Identification Conditions,","venue":null,"work_id":"79ae8b1e-449c-430a-9f17-eaa0d1b608c9","year":2022},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:19.704586Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:507f159a480d629c1940f77d372a8d7079af5fa253c93396713a51bccc587fe8","observation_id":"e9b4f93f-f91e-4efb-947d-74f88efdecef","resolution":{"observed_at":"2026-08-07T11:11:28.426701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.414087Z","title":"Toward a Clearer Definition of Selection Bias When Estimating Causal Effects,","venue":null,"work_id":"1274ebfe-c97d-423e-99ad-e2457e7d5fac","year":2022},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:19.762108Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:fdbb8c3c1d1d4cfe298d4939736dc5b6de7b36d229680563dc1144b79db22418","observation_id":"d9b6b186-88be-4950-a542-7b0bf161f46a","resolution":{"observed_at":"2026-08-07T11:11:28.417386Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.404149Z","title":"Selection Bias Requires Selection: The Case of Collider Stratification Bias,","venue":null,"work_id":"039b85db-aef4-4e80-a333-409f99b73820","year":2023},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:19.851164Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:c8d741578538ab7c50a8c97a07a1329693901bba457a23b988f46484fa104ab8","observation_id":"248e8c10-4efd-4e6d-88fd-6675145aff4f","resolution":{"observed_at":"2026-08-07T11:11:28.407869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.394774Z","title":"The Evolution of Selection Bias in the Recent Epidemiologic Literature—A Selective Overview,","venue":null,"work_id":"9e44d957-55a9-4187-ae2d-e001f539fefd","year":2024},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:19.925548Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:004e69e9595fc3745626b401ff079b8b131c47b640bc9dbfe6f360554d916a0b","observation_id":"c72efa87-04e0-4779-80b4-65d79ee6e52a","resolution":{"observed_at":"2026-08-07T11:11:28.397889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.384929Z","title":"A Potential Outcomes Approach to Selection Bias,","venue":null,"work_id":"4541bd68-e24a-46f7-940d-b7e4ad31c901","year":2023},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.028354Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:1a35a241f57b2c5139b4cfe34ac482cf7d6b46581b4b99ef88924f3df29fa1d4","observation_id":"50c0babe-10b9-4e03-9193-1f1fd109dca6","resolution":{"observed_at":"2026-08-07T11:11:28.388062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.375417Z","title":"Simple graphical rules for assessing selection bias in general-population and selected-sample treatment effects,","venue":null,"work_id":"5fa5a9c9-25f9-41b8-9730-1a289b39bb15","year":2024},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.104614Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:6cfcb3ffb289d7dec49d19e3c9624fe9435abc9008c8baa6a36469bedadd7dae","observation_id":"e853b045-ace3-4a45-952a-9fdf061023fb","resolution":{"observed_at":"2026-08-07T11:11:28.378638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.365939Z","title":"Marginal structural models and causal inference in epidemiology,","venue":null,"work_id":"4dfbb3e8-db48-4eb3-b45e-3d8db9ec232b","year":2000},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.175023Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:f3e6c6b8703d88963102f49dff1332c4817e8eba449722d8ecf683dcb97f7ecf","observation_id":"1fda97c1-8681-4633-bb1b-f5ef48bf1785","resolution":{"observed_at":"2026-08-07T11:11:28.369022Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.355994Z","title":"Estimating marginal structural model parameters for time-fixed, binary actions with g-computation and estimating equations,","venue":null,"work_id":"2179a386-c692-478f-8d8a-e6cad3e19568","year":2025},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.245833Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:6ca06671e0f0413a5869030d9afbc035ae40dd71ceac992c53c4212e2076fb75","observation_id":"e4d72eee-8a97-4c05-8c34-f8e84368df06","resolution":{"observed_at":"2026-08-07T11:11:28.359697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.346612Z","title":"Reflection on modern methods: combining weights for con- founding and missing data,","venue":null,"work_id":"e2acf241-2bf1-4b92-a404-5e785008db87","year":2021},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.319179Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:ef807b70dd5c971f23557ba615fbba7bfd829639321eb7dd874f812259c87e5c","observation_id":"9051dd3a-64b3-4c4b-b825-d19f758405a9","resolution":{"observed_at":"2026-08-07T11:11:28.349924Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/9781118445112.stat08068","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:25.805965Z","title":null,"venue":null,"work_id":"96e12727-1e8f-4434-b8e9-9b06b7be4f23","year":2018},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.381180Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:fe21de79088611b18ca3d9d19268a0548c06118e3a48d995d62d30b9047b523d","observation_id":"0702d4f2-f821-43bc-b9df-f0b52222673f","resolution":{"observed_at":"2026-08-07T11:11:25.867616Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.337379Z","title":"Implementation of G-computation on a simulated data set: demonstration of a causal inference technique,","venue":null,"work_id":"5cf5445c-4db0-460a-9cc4-7f0ce1f324c7","year":2011},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.444471Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:fdcee1e04248791e85d4576e688cfe971b50e2868b8a65a21ae277d88523fa39","observation_id":"2a7e1500-3da0-4aaf-91cb-4da5924ede0a","resolution":{"observed_at":"2026-08-07T11:11:28.340499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.327006Z","title":"G-computation, propensity score-based methods, and targeted maximum likelihood estimator for causal inference with different covariates sets: a comparative simulation study,","venue":null,"work_id":"9c6baccb-d3c2-47cf-b1b5-64740f0b6c81","year":2020},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.499235Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:722dacc0cc09574edba33a4dc825e4c29e9b460b0792afe28b7856d441ddf7c8","observation_id":"1474929e-9264-4e7e-9ff1-c269ba9ecadd","resolution":{"observed_at":"2026-08-07T11:11:28.330523Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.317405Z","title":"A Practical Example Demonstrating the Utility of Single-world Intervention Graphs,","venue":null,"work_id":"96380b83-e0ca-436b-b84c-fd24abad2594","year":2018},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.560344Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:7a839d12f1e5dc7734e1ba66bd03a528a4f248a280dda94e39a47ea5e2496b5e","observation_id":"bfd26e41-7616-4e24-b22f-1e7edbf132b2","resolution":{"observed_at":"2026-08-07T11:11:28.320660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.308766Z","title":"The Calculus of M-Estimation,","venue":null,"work_id":"e957fcfb-b41b-400a-bf95-7ae9551ad6c3","year":null},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.652186Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:a15745762d2980bcc0d04b4744c246a5b6e33c7dc4c33c9da3663020f109c5f2","observation_id":"08168ec3-0c7e-4d61-ba4b-eec89df39b82","resolution":{"observed_at":"2026-08-07T11:11:28.311916Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-1-4614-4818-1","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:25.618794Z","title":null,"venue":null,"work_id":"22030d3f-0058-4f9e-99db-4dd841320ab5","year":2013},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.765930Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:18ac62677c3183e12029e2a4f3fadbb70f5a102e2d6c9ed59410e85e40a6d622","observation_id":"7a70614e-8144-423d-a128-12ba72641d4b","resolution":{"observed_at":"2026-08-07T11:11:25.707514Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.299715Z","title":"M-estimation for common epidemiological measures: intro- duction and applied examples,","venue":null,"work_id":"2924d729-b780-417c-97d5-e0ebdd4d11b4","year":2024},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.829356Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:9b455d0d388a427ad71a845f28b10639ad36f56fa153857e669cc66253f27b49","observation_id":"c86f13e3-ca89-4ebb-a1c2-2bf93f0c39c8","resolution":{"observed_at":"2026-08-07T11:11:28.302938Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/9781118445112.stat01932","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:25.364047Z","title":"Estimating Equations, Theory of,","venue":null,"work_id":"2771f8cd-50b0-451a-b958-6ff9deaeb507","year":2014},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.886634Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:452bdb090c2e95b6dfaf1ab8a5bb3779928cb2409682bdbb94127b7f3308f192","observation_id":"052fce85-22ef-4b94-8dfb-6f599f6f9cda","resolution":{"observed_at":"2026-08-07T11:11:25.512221Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.290011Z","title":"Estimating functions and the generalized method of moments,","venue":null,"work_id":"dcfe6b0a-2970-43a1-9b97-e6e6906148f3","year":2011},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.946528Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:2f0669d4062c6334ae81c0e543da595c0a01f6e1c02a183ae52f27a558c9985d","observation_id":"b8fd6f7b-b908-4a9f-81b1-895dbe31728d","resolution":{"observed_at":"2026-08-07T11:11:28.293050Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.280846Z","title":"Carroll, David Ruppert, Leonard A","venue":null,"work_id":"2b64351b-0691-42a3-8204-4572d2fc4ae6","year":2006},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.003320Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:9af4dd56ceb279b6698fc7d3857e847cd3b76845dc975f17243d1d2cdee5c9ef","observation_id":"a0aee241-0f6f-4781-90da-cd15d4c564bc","resolution":{"observed_at":"2026-08-07T11:11:28.283963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.271605Z","title":"Bootstrap Methods: Another Look at the Jackknife,","venue":null,"work_id":"67e6b2f1-358a-4cdb-9327-89d4b571a3c6","year":1979},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.092860Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:b6f8689fd2d53599f4baf41f94de4fc8a4d407ab19b6c1784de21b3d48bce1e8","observation_id":"14771751-11eb-4dcc-a1e8-7c2684092f53","resolution":{"observed_at":"2026-08-07T11:11:28.275021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.262017Z","title":"Sampling distributions and the bootstrap,","venue":null,"work_id":"e027cd3c-4fc1-4456-81c8-1018ec487cbc","year":2015},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.138208Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:2e8aa33f3e0adb57ba295bb1da1bb1f729a47f50348ab1f636d9f119fb1ed166","observation_id":"e90cb830-9335-4f4f-9221-b81435d85874","resolution":{"observed_at":"2026-08-07T11:11:28.265032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.252607Z","title":"On Variance of the Treatment Effect in the Treated When Estimated by Inverse Probability Weighting,","venue":null,"work_id":"2c1949e0-503b-480b-a067-f8bed684ebdc","year":2022},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.210545Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:107931ab6ba7eb2bf3612b781a1d21f49dc8cbfa51ed83092bacb276a5db3b08","observation_id":"8d31fdc6-34ce-4173-89d5-b34e62104e56","resolution":{"observed_at":"2026-08-07T11:11:28.255960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.11300","last_updated":"2022-10-10T20:37:32Z","snapshot_observed_at":"2026-08-02T21:13:25.026363Z","submitted_at":"2022-03-21T19:17:26Z","title":"Delicatessen: M-Estimation in Python","version":3},"cited_work":{"arxiv_id":"2203.11300","doi":null,"metadata_source":"pith","pith_arxiv_id":"2203.11300","snapshot_observed_at":"2026-08-07T11:11:26.142713Z","title":"Delicatessen: M-Estimation in Python","venue":"stat.ME","work_id":"de875c75-ac99-4402-b3d9-0bb1b31a2014","year":2022},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.268406Z"},"links":{"cited_paper":"/paper/2203.11300","citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:c72c10c7cab6d7c3b1b6dc91a9f4f008b63ce9063e0913e3975f67c2ea75e93a","observation_id":"7b509cdd-e0cd-4b71-a47f-03579b76b7af","resolution":{"observed_at":"2026-08-07T11:11:26.253737Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.242586Z","title":"The Calculus of M-Estimation in R with geex,","venue":null,"work_id":"7a532933-e94a-4a9c-9d5c-f237fc008142","year":2020},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.319706Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:f7e08fc766c40e46842a7db2a4b5677b396723eabe4a3be44f6e869acdfde48b","observation_id":"fc2666ff-f2aa-40e7-aab0-415a8ee0917f","resolution":{"observed_at":"2026-08-07T11:11:28.246106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.232248Z","title":"Estimating causal effects from epidemiological data,","venue":null,"work_id":"dba79027-f51f-42d8-b4e4-af77d2009b46","year":2006},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.390104Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:cab2fec134c5fb5de2f03590533a04d03a16360d546b5f3e041ee9318e62e674","observation_id":"6108a031-68ab-4ea1-8b04-5fe2c8959fbc","resolution":{"observed_at":"2026-08-07T11:11:28.235666Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.222034Z","title":"The consistency statement in causal inference: a definition or an assumption?,","venue":null,"work_id":"7bf3274f-e9a9-4905-95ac-377af651672f","year":2009},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.474119Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:0329ef269a75e757c28acb8e52fe585235fff9f423f056a4b327211f6a6a8983","observation_id":"537ea3ec-348c-4b48-ace2-33fe646fafe0","resolution":{"observed_at":"2026-08-07T11:11:28.225407Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.05010","last_updated":"2022-07-11T16:59:15Z","snapshot_observed_at":"2026-08-01T17:15:00.789138Z","submitted_at":"2022-07-11T16:59:15Z","title":"Positivity: Identifiability and Estimability","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.05010","snapshot_observed_at":"2026-08-07T11:11:21.528967Z","title":"Positivity: Identifiability and Estimability,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.528967Z"},"links":{"cited_paper":"/paper/2207.05010","citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:312a67e487003f81d4f90fc309e5a1e6cfaa884789a4ab84987b528c5bb099ab","observation_id":"166d3431-9f7d-4c02-801b-f42971253a27","resolution":{"observed_at":"2026-08-07T11:11:21.528967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:21.593716Z","title":"Using simulation studies to evaluate statistical methods,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.593716Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:bfa0d9453a29634bafdcb651e9b7df2a5f6505557ec466ff3f85cdf036380011","observation_id":"62c2fa32-f8b6-43c7-b6bf-797802f65b11","resolution":{"observed_at":"2026-08-07T11:11:21.593716Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.212075Z","title":"Array programming with NumPy,","venue":null,"work_id":"64877ea7-aa9f-481e-9d4c-26f12a225673","year":2020},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.646530Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:73ab4e1400094e95a966e79dfd63582e84922dfcd563146ef2bd2e582c67fc6d","observation_id":"087045b0-7736-4976-a6f7-8664d533f3c9","resolution":{"observed_at":"2026-08-07T11:11:28.215183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.202178Z","title":"Scipy 1.0: fundamental algorithms for scientific computing in Python,","venue":null,"work_id":"56b17b29-8b19-456c-8c05-c5070a480550","year":2020},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.715302Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:008541cbce15adcd45a571ad4490c52e74cb51b4f7304de19678891aa5bc2db3","observation_id":"9eb9b806-f179-4df4-a480-5c84ffeb7b15","resolution":{"observed_at":"2026-08-07T11:11:28.205342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.191357Z","title":"Data Structures for Statistical Computing in Python,","venue":null,"work_id":"7c7ae3e0-0abe-4a79-bb7e-2b0c8c00204d","year":2010},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:21.903753Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:113d6934aeb1cdfe16ee409e4852bdb2a2deefd972d9fe3004af7d7fa1a745b8","observation_id":"2828a65c-8c49-4b61-b14c-78fa2e77ce36","resolution":{"observed_at":"2026-08-07T11:11:28.195282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/sim.10255","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:25.198222Z","title":"Empirical Sandwich Variance Estimator for Iterated Conditional Expectation g-Computation,","venue":null,"work_id":"d6e1f895-41f5-4154-aef3-883cd7e2af61","year":2024},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:22.123031Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:8f1df5f2a6b9a8d53eaf3b5ac70d62792f5a842dc7679e6c808e52ef27a14e61","observation_id":"74b65a36-e706-4508-bfb0-f04e629ca576","resolution":{"observed_at":"2026-08-07T11:11:25.297559Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.182354Z","title":"Leveraging external validation data: the challenges of transporting measurement error parameters,","venue":null,"work_id":"4f66e91a-1a9b-4d8b-97dc-5b3f177a2fb1","year":2024},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:22.278044Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:5b4c7b26836fcccda8fa4fe4d08ba0a28432eda3231498c8f88b5bb60a61e3dd","observation_id":"51435b0f-8a7d-4c5e-baa2-7cc5b9598f65","resolution":{"observed_at":"2026-08-07T11:11:28.185487Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.172485Z","title":"Targeted Learning of the Mean Outcome under an Optimal Dynamic Treatment Rule,","venue":null,"work_id":"118b7154-49a6-4526-84d8-9df85ed44738","year":2015},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:22.477251Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:4cf6939ac01f3fac5adc9ed416d0b9f7eef84c1e654116e9179802b7587fd257","observation_id":"d89f840e-aa3a-4db0-9adf-77bfdf50edf7","resolution":{"observed_at":"2026-08-07T11:11:28.175845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.163304Z","title":"Synthesis estimators for transportability with positivity violations by a continuous covariate,","venue":null,"work_id":"768fc81b-9059-45a1-986a-76569a185d59","year":2024},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:22.608388Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:b1c95f800d9903f56909168ac3870f9ee4a0ea0c8c1447a45d6067ce1645191d","observation_id":"2625e69b-1ef1-4ad8-9878-70817394713b","resolution":{"observed_at":"2026-08-07T11:11:28.166298Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.154141Z","title":"Econometric methods for fractional response variables with an application to 401(k) plan participation rates,","venue":null,"work_id":"36e440cf-a44e-41d5-b133-7ffd31ffd4cc","year":1996},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:22.828367Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:b99480e9f399d2e2c59190187ed153ca91fdb7cf59bd0ffb86babbb78dda0be6","observation_id":"86166643-5400-446c-bd71-d0141cbd7411","resolution":{"observed_at":"2026-08-07T11:11:28.157284Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:28.086850Z","title":"Quasi-Likelihood and Optimal Estimation,","venue":null,"work_id":"526e4e31-91d2-4b04-9403-539a72c86fd1","year":1987},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:23.035895Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:0a959fc8021293646cf370ca685248c98d566b6356e0478034c3a0a044d9eb34","observation_id":"8bc82ac2-5495-4f99-9588-f7bb3ebfc0ca","resolution":{"observed_at":"2026-08-07T11:11:28.127008Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:27.994388Z","title":"Revisiting representativeness,","venue":null,"work_id":"db3d9adc-65e4-4b18-a374-389d8ea1988c","year":2024},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:23.137652Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:ad3a2434144a9b096bd261e04c91cb070d8024dd60bbeddf3f6659a17fba3163","observation_id":"f77445de-0615-4bfc-88d7-9f9dc67cdb34","resolution":{"observed_at":"2026-08-07T11:11:28.013972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:23.230914Z","title":null,"venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:23.230914Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:4c9cda72ecaa00b67d69916ae66758f779c99c2f0e21674901c9af0306b87d59","observation_id":"63a6eddd-29e0-4f22-b08b-fb760e1906d1","resolution":{"observed_at":"2026-08-07T11:11:23.230914Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:27.797044Z","title":"Z-estimation and stratified samples: application to survival models,","venue":null,"work_id":"04c8d4fe-9652-43a9-ba51-e4e758e8bcfd","year":2015},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:23.369808Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:df818475932606a6bf60ae7cc4afc6e00958df645fb51604af95da27b893798c","observation_id":"0e2df23e-5438-42cf-bb08-387460ff0bc5","resolution":{"observed_at":"2026-08-07T11:11:27.885205Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.13291","last_updated":"2026-06-03T15:16:16Z","snapshot_observed_at":"2026-08-07T16:01:19.604771Z","submitted_at":"2025-04-17T19:04:07Z","title":"Estimating equations for causal survival analysis with pooled logistic regression","version":2},"cited_work":{"arxiv_id":"2504.13291","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.13291","snapshot_observed_at":"2026-08-07T11:11:25.974545Z","title":"Estimating equations for causal survival analysis with pooled logistic regression","venue":"stat.ME","work_id":"70458759-247e-49c0-a7eb-e1c961bae5f6","year":2025},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:23.438382Z"},"links":{"cited_paper":"/paper/2504.13291","citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:aceccc7d804df9f6f8ad2bf908e898395ce889bdd8afc9158e4ed64a07635feb","observation_id":"53c316d3-d823-4e83-928e-f78b0b9ef0ce","resolution":{"observed_at":"2026-08-07T11:11:26.069266Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:27.648094Z","title":"The Robust Inference for the Cox Proportional Hazards Model,","venue":null,"work_id":"2a202b87-ab64-4ad0-9f2d-319559b39d70","year":1989},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:23.578971Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:9ff988f15ecfff737825d5c93df21cfc8373d6c0637a5e496a1b255f90c9acd9","observation_id":"9c40a3cd-352f-4924-a7db-801d49d61631","resolution":{"observed_at":"2026-08-07T11:11:27.728219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:27.511045Z","title":"Penalized Regressions: The Bridge versus the Lasso,","venue":null,"work_id":"6a0d6c15-f4cd-43f6-9a53-a360e14d1559","year":1998},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:23.641406Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:8bbb99d660c4d6b387619f022febbf6722abd0660e847875cbf29a09cc6f3acb","observation_id":"b4d42ecb-5047-4b5b-bdd6-fa4789a0a0f7","resolution":{"observed_at":"2026-08-07T11:11:27.576149Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:27.490616Z","title":"Penalized Estimating Equations,","venue":null,"work_id":"e6607b84-d932-4c78-aed2-55f3ff9e1113","year":2003},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:23.750947Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:296a4b75f26a2f3a99fb2f74e200fe7815a7c6ac44d9ec0fa3a88e2b46e19395","observation_id":"8980389d-5360-4296-a527-2893ae5dad92","resolution":{"observed_at":"2026-08-07T11:11:27.493967Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:27.446264Z","title":"A unified class of penalties with the capability of producing a differentiable alternative to l1 norm penalty,","venue":null,"work_id":"9bc93f35-76ec-4a4a-a17f-55c8a1e06ec3","year":2019},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:23.899376Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:5f1746c4cf955b29b532e7f93e8f1bb7ce6c66a1c82e8702a8415b17095b3175","observation_id":"f9141596-b726-43cd-9327-b1b6de12a438","resolution":{"observed_at":"2026-08-07T11:11:27.462847Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.02826","last_updated":"2020-07-21T01:48:09Z","snapshot_observed_at":"2026-07-06T07:44:03.990575Z","submitted_at":"2019-04-04T23:46:44Z","title":"What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.02826","snapshot_observed_at":"2026-08-07T11:11:23.955854Z","title":"What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems,","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:23.955854Z"},"links":{"cited_paper":"/paper/1904.02826","citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:46c25b219f67ddfbab46c026ca93a31e7e3770312e2610e1e0555e0cdceb1af8","observation_id":"a317fee4-7f42-4ffd-8f5a-dccfa7212fb2","resolution":{"observed_at":"2026-08-07T11:11:23.955854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.11342","last_updated":"2021-09-27T03:41:00Z","snapshot_observed_at":"2026-07-06T11:41:28.272848Z","submitted_at":"2021-08-25T16:54:19Z","title":"Nonparametric identification is not enough, but randomized controlled trials are","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.11342","snapshot_observed_at":"2026-08-07T11:11:24.044512Z","title":"Nonparametric identification is not enough, but randomized controlled trials are,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:24.044512Z"},"links":{"cited_paper":"/paper/2108.11342","citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:9ecfd800e0daa670ecea22d012e045c591ff844ab0f5372c840c672c46cb854a","observation_id":"3eca9b43-27bf-445d-ae0b-38b700d24e5c","resolution":{"observed_at":"2026-08-07T11:11:24.044512Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:27.301413Z","title":"Targeted maximum likelihood estimation for causal inference in observational studies,","venue":null,"work_id":"ec8b334c-6e28-43e1-98fc-e0cf74ce6857","year":2017},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:24.163917Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:1add557ff03e08cf7f910de671b27420f7412e277bcce92ccd42c8be9d98d7b5","observation_id":"26f20c05-daf7-4d75-8aea-a686a363adbb","resolution":{"observed_at":"2026-08-07T11:11:27.382093Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:27.199058Z","title":"Doubly robust estimation of causal effects,","venue":null,"work_id":"5dc3e2e5-0ae5-4583-8842-4d6d59356272","year":2011},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:24.282025Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:4e8753b36dd9d3f321ae6f17325e1b37a2240ca0d6891f8a7dd9a1ae71b45f7c","observation_id":"bf7d6954-069f-45e0-aa66-e05287603c96","resolution":{"observed_at":"2026-08-07T11:11:27.233199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:27.069326Z","title":"Demystifying Statistical Learning Based on Efficient Influence Functions,","venue":null,"work_id":"5e2b51a8-010a-4adc-933a-ddb49045cd3d","year":2022},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:24.411424Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:2cc47688fd80c3eaa12430a2b4ce6866613f19131c75cb64662d1f5e10a02843","observation_id":"159206fb-b939-4f6e-a15c-e5ac57712557","resolution":{"observed_at":"2026-08-07T11:11:27.137149Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05363","last_updated":"2025-02-07T22:28:25Z","snapshot_observed_at":"2026-07-06T20:33:11.256513Z","submitted_at":"2025-02-07T22:28:25Z","title":"Pulling back the curtain: the road from statistical estimand to machine-learning based estimator for epidemiologists (no wizard required)","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.05363","snapshot_observed_at":"2026-08-07T11:11:24.521630Z","title":"Pulling back the curtain: the road from statistical estimand to machine-learning based estimator for epidemiologists (no wizard required),","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:24.521630Z"},"links":{"cited_paper":"/paper/2502.05363","citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:63f27556c55229274deb08d6510050934d32c5785f1241b53d736fb5cb8843b1","observation_id":"1dfa625f-9da8-472c-aea7-d9b8145be93c","resolution":{"observed_at":"2026-08-07T11:11:24.521630Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:26.932883Z","title":"Five Facts About Influence Functions,","venue":null,"work_id":"509defb7-5930-4ce6-8f6e-c7d010ec8a8a","year":2025},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:24.587469Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:8c3cd783c64df7bc8d1377cdd2fb6fc92b0cbc1a04170403ed5a792120cd0e03","observation_id":"ce9e0603-b732-424c-8992-160f56e473af","resolution":{"observed_at":"2026-08-07T11:11:27.019385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:26.813216Z","title":"Double robust variance estimation with parametric working models,","venue":null,"work_id":"aaa1f20c-a590-40af-af6e-acd36ffd4570","year":2025},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:24.762719Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:6327875de0c6c1cbf67176709b0eeda2454349bb55420f3c215e7861442fa32a","observation_id":"7fdd46b2-2ca8-4b0c-801b-014b48db9542","resolution":{"observed_at":"2026-08-07T11:11:26.880342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:26.764530Z","title":"Double/debiased machine learning for treatment and structural parameters,","venue":null,"work_id":"d1bf5eab-afc9-465d-828e-fd284adc9b0b","year":2018},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:24.779840Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:99784f971c774973ab9e8fd0e5bedf3cecbe36fa1c9954017bbfc8c9963caa0f","observation_id":"3585d1bf-44b6-4c61-b516-324e11769eda","resolution":{"observed_at":"2026-08-07T11:11:26.769020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:26.649953Z","title":"Machine Learning for Causal Inference: On the Use of Cross-fit Estimators,","venue":null,"work_id":"a1733fec-10d0-4c41-b460-fb1858bbd4de","year":2021},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:24.865354Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:1998d9a12ef1b822361714b5903a2aaddb47a17759390a81d373b38924f140d9","observation_id":"03125a1f-da4f-496c-93e1-6eaaab3fd585","resolution":{"observed_at":"2026-08-07T11:11:26.712429Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:26.538154Z","title":"Machine Learning and Causal Inference,","venue":null,"work_id":"c723d0fa-c168-4fe0-86a0-00de9a54a26c","year":2022},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:24.948302Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:79cca4de59b16cefa544b44236905a0510a2caed039deec66700e2c8c6b6bf9a","observation_id":"aabc86a7-f8cb-4943-b671-43e347efe68d","resolution":{"observed_at":"2026-08-07T11:11:26.586049Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:26.330158Z","title":"The use of plasmodes as a supplement to simulations: a simple example evaluating individual admixture estimation methodologies,","venue":null,"work_id":"bec040b9-6918-4a63-848a-654da5c22bf3","year":2009},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:25.050455Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:9d34a350e5d7a6842674a7fadcde57ac5b42fd704a76ea41fd36116c3caf4944","observation_id":"e29ba5a3-9f67-468f-b461-3dec5bed6a8c","resolution":{"observed_at":"2026-08-07T11:11:26.439273Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:20.708199Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias","version":2},"reference_index":2002,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:20.708199Z"},"links":{"citing_paper":"/paper/2506.03347"},"observation_digest":"sha256:a30a646131b396a729268bb76731d85aa982772b540a6d3b5b69dd4a0e659144","observation_id":"c2cc36e1-c01b-4076-85a4-e3180a348e89","resolution":{"observed_at":"2026-08-07T11:11:20.708199Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.03347","last_updated":"2025-07-31T14:18:36Z","latest_version":2,"primary_category":"stat.ME","snapshot_observed_at":"2026-08-07T11:03:03.419185Z","submitted_at":"2025-06-03T19:38:43Z","title":"Constructing g-computation estimators: two case studies in selection bias"},"reference_resolution":{"displayed":58,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":6,"verified_fuzzy":44},"total_outbound_references":58},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2506.03347."}