{"as_of":"2026-08-08T16:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:36ffa6cb2d1d571a4f23bc54507ae925c0a7171d05518491a4556662d3429a24","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":19,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":19,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":19,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":19,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:51:17.040316Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":35,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-07T05:51:17.040316Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.07140","last_updated":"2025-06-08T13:37:38Z","snapshot_observed_at":"2026-08-07T05:38:55.820011Z","submitted_at":"2025-06-08T13:37:38Z","title":"Quantile-Optimal Policy Learning under Unmeasured Confounding","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-07T05:51:17.040316Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2506.07140"},"observation_digest":"sha256:d4e4ff973f9fbbef5294975fdf75beab6a253c7a37d5307ea3c5eea97b1e7bb1","observation_id":"70ec07fa-16df-4bd1-adff-b0fedb3f863b","resolution":{"observed_at":"2026-08-07T05:51:17.040316Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-06T17:14:06.126936Z","title":"An introduction to proximal causal learning.arXiv preprint arXiv:2009.10982, 2020","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.11381","last_updated":"2025-07-16T10:38:29Z","snapshot_observed_at":"2026-08-06T17:06:49.161861Z","submitted_at":"2025-07-15T14:50:41Z","title":"From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies","version":2},"reference_index":138,"source":"pdf_text","source_observed_at":"2026-08-06T17:14:06.126936Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2507.11381"},"observation_digest":"sha256:e792d428f07f7a290aee753bf754ecf5e976484ea6c4b0c3b01f0fcc2f6dd702","observation_id":"4842a0fa-0c5e-4576-b786-1198cccf6c1c","resolution":{"observed_at":"2026-08-06T17:14:06.126936Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T17:02:40.453293Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.17181","last_updated":"2025-08-24T01:30:39Z","snapshot_observed_at":"2026-08-07T23:33:09.671285Z","submitted_at":"2025-08-24T01:30:39Z","title":"Source-Condition Analysis of Kernel Adversarial Estimators","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-05T17:02:40.453293Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2508.17181"},"observation_digest":"sha256:6f020703f5984c269db20db8464eedd0057d061f5bd61770427845e0e0718850","observation_id":"3a03cc51-f3dd-49b8-b14c-f9648c7817c6","resolution":{"observed_at":"2026-08-05T17:02:40.453293Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2602.09969","last_updated":"2026-05-14T03:09:09Z","snapshot_observed_at":"2026-08-06T08:58:33.647066Z","submitted_at":"2026-02-10T16:58:50Z","title":"Causal Multi-Task Demand Learning","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-16T02:23:37.433336Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2602.09969"},"observation_digest":"sha256:74269e70712afa61640a691d4ca4cb8d587f7e1e8235df411cfee0394c7a6d7c","observation_id":"3bfb7c0e-72f5-4c3e-aef4-b7e6388b0564","resolution":{"observed_at":"2026-05-16T02:27:09.768326Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2605.02112","last_updated":"2026-05-04T00:22:21Z","snapshot_observed_at":"2026-08-08T11:49:37.917380Z","submitted_at":"2026-05-04T00:22:21Z","title":"An adaptive variance estimator for relative sparsity","version":1},"reference_index":164,"source":"arxiv_source","source_observed_at":"2026-05-08T19:35:46.097113Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2605.02112"},"observation_digest":"sha256:cf6c239ef0a130a17fc497e703fbf1f06a0c6d61011ed9f41fcd969b28a46a88","observation_id":"a30b13b7-8577-4d9b-837b-59fe36320912","resolution":{"observed_at":"2026-05-09T05:45:22.561139Z","resolver_source":"arxiv_id","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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2605.09462","last_updated":"2026-05-10T10:24:00Z","snapshot_observed_at":"2026-07-06T23:21:35.327066Z","submitted_at":"2026-05-10T10:24:00Z","title":"Proximal Path-Specific Inference","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-12T05:09:02.141355Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2605.09462"},"observation_digest":"sha256:df0b98cb91dfbbc40c617cee02940dd0a935ed3e463dc192ce1906666c19cf10","observation_id":"d3134835-4406-46ae-b153-636f5e7ceb2b","resolution":{"observed_at":"2026-05-12T05:36:25.070344Z","resolver_source":"arxiv_id","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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2605.19006","last_updated":"2026-07-08T02:00:58Z","snapshot_observed_at":"2026-07-12T16:32:57.686755Z","submitted_at":"2026-05-18T18:28:16Z","title":"Causal Inference with Categorical Unobserved Confounder via Mixture Learning","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-05-20T07:56:53.501281Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2605.19006"},"observation_digest":"sha256:ba2198a67386ada6e31ab3ad916164ab426a2a1247f7617925c0051150f47b1a","observation_id":"3f587f6e-8852-4b61-92a2-13320d3cdbbb","resolution":{"observed_at":"2026-05-20T07:58:07.679552Z","resolver_source":"arxiv_id","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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2605.20767","last_updated":"2026-05-20T06:09:41Z","snapshot_observed_at":"2026-08-02T14:38:35.950771Z","submitted_at":"2026-05-20T06:09:41Z","title":"The Illusion of Intervention: Your LLM-Simulated Experiment is an Observational Study","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-05-21T05:21:23.309963Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2605.20767"},"observation_digest":"sha256:14d3e9756da31960deb23173eb03f6b95b52f2deb10532bc52c85e4f934c147b","observation_id":"a59618ca-7157-4372-a449-443243ee57b9","resolution":{"observed_at":"2026-05-21T05:23:58.333883Z","resolver_source":"arxiv_id","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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2606.01214","last_updated":"2026-07-30T05:01:17Z","snapshot_observed_at":"2026-08-07T14:58:09.559456Z","submitted_at":"2026-05-31T13:03:58Z","title":"Conditioning-Depth Diagnostics for Hidden Memory in Temporal Causal Discovery","version":1},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-06-28T16:10:19.459683Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2606.01214"},"observation_digest":"sha256:5241fd098127b4f54695263972ef0ed69e234288afb17bf6016038f77fbe6bec","observation_id":"cb30d54e-7b1e-4a33-baf8-5aaaaee519ef","resolution":{"observed_at":"2026-06-28T16:12:21.959810Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-03T00:54:27.006315Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.01214","last_updated":"2026-07-30T05:01:17Z","snapshot_observed_at":"2026-08-07T14:58:09.559456Z","submitted_at":"2026-05-31T13:03:58Z","title":"Conditioning-Depth Diagnostics for Hidden Memory in Temporal Causal Discovery","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T00:54:27.006315Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2606.01214"},"observation_digest":"sha256:7702d0ff8edbd0ec95954640b15f1b7bad883b17d69b2d915f6887d384b5b609","observation_id":"d46c2ebb-3ed7-4c16-a06c-a70a28ae48d1","resolution":{"observed_at":"2026-08-03T00:54:27.006315Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2606.17600","last_updated":"2026-06-16T07:07:06Z","snapshot_observed_at":"2026-08-07T22:07:05.993208Z","submitted_at":"2026-06-16T07:07:06Z","title":"Proximal Mediation Analysis with Hidden Recanting Witnesses","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-06-26T23:45:37.438795Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2606.17600"},"observation_digest":"sha256:c8bc789cfd313e4097ea476ab51e2c14686a2f25ed376a4e36c13ad72ed2f955","observation_id":"615e090a-c67b-496a-a8aa-8aa91858ccb1","resolution":{"observed_at":"2026-07-03T22:08:59.245815Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2606.18535","last_updated":"2026-06-16T23:03:42Z","snapshot_observed_at":"2026-07-06T23:53:59.519305Z","submitted_at":"2026-06-16T23:03:42Z","title":"Shrinkage priors for Bayesian Substitute Confounders","version":1},"reference_index":242,"source":"arxiv_source","source_observed_at":"2026-06-26T23:01:57.987232Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2606.18535"},"observation_digest":"sha256:0e94bd96341d56b8a888530b93a2a489bb30826ba9a635a8903af8ce209bba28","observation_id":"afb9b516-e06c-4679-970d-6f7ae713fcac","resolution":{"observed_at":"2026-07-03T23:09:01.031337Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2606.19361","last_updated":"2026-06-08T19:39:59Z","snapshot_observed_at":"2026-07-06T23:54:41.980696Z","submitted_at":"2026-06-08T19:39:59Z","title":"Computational Identifiability","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-06-27T16:52:27.577269Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2606.19361"},"observation_digest":"sha256:b4caf31286dfe3ecf94237f7e99caff07053843fbbe66bf9e53b9491e7a358f3","observation_id":"7484219e-b398-4a2b-9e62-c7f2ef31974c","resolution":{"observed_at":"2026-07-03T00:57:30.564970Z","resolver_source":"arxiv_id","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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2606.20206","last_updated":"2026-06-18T13:19:43Z","snapshot_observed_at":"2026-08-06T08:02:19.305046Z","submitted_at":"2026-06-18T13:19:43Z","title":"Off-Policy Evaluation for Missingness-Aware Policies in MDPs with Rewards Missing Not at Random","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-06-26T15:38:16.806415Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2606.20206"},"observation_digest":"sha256:3814bbb5b92f356489b6b048b8eb2c3a003026b2ec313b7c557a79a12e09898f","observation_id":"54a57f62-f958-4932-88a1-5680fb8cb8e6","resolution":{"observed_at":"2026-07-04T05:39:40.753817Z","resolver_source":"arxiv_id","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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2606.27114","last_updated":"2026-06-25T14:49:50Z","snapshot_observed_at":"2026-08-06T22:59:29.445064Z","submitted_at":"2026-06-25T14:49:50Z","title":"Cross-Head Attention Uplift Network with Inverse Propensity Score under Unobserved Confounding","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-26T05:14:37.758306Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2606.27114"},"observation_digest":"sha256:8004426589299368870991637d506ac52669381f2d4c027e055c4aba9f149f82","observation_id":"7f4b7de4-65cd-4b30-a2f6-0cddd52d20db","resolution":{"observed_at":"2026-07-04T13:29:50.857130Z","resolver_source":"arxiv_id","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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2606.30648","last_updated":"2026-06-05T04:37:53Z","snapshot_observed_at":"2026-07-07T00:04:29.879877Z","submitted_at":"2026-06-05T04:37:53Z","title":"MediEncoder: Nonlinear Representation Learning for High-Dimensional Causal Mediation Analysis","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-07-01T07:21:21.953558Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2606.30648"},"observation_digest":"sha256:ed978de3df05d09aca17bf720d0a563821c0d453ac4508c57aa156f926e7f696","observation_id":"83ef54fc-4265-4b04-bc2f-dfe026a289f3","resolution":{"observed_at":"2026-07-01T08:35:34.190311Z","resolver_source":"arxiv_id","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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":"2009.10982","doi":"10.48550/arxiv.2009.10982","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":"arXiv (Cornell University)","work_id":"803b8852-444b-460b-b2fe-605197636e55","year":2020},"citing_paper":{"arxiv_id":"2607.00222","last_updated":"2026-06-30T22:00:38Z","snapshot_observed_at":"2026-08-03T08:19:19.256329Z","submitted_at":"2026-06-30T22:00:38Z","title":"Causal Inference for All: Marginal Estimands for Outcomes Truncated by Death","version":1},"reference_index":183,"source":"arxiv_source","source_observed_at":"2026-07-02T17:27:17.001264Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2607.00222"},"observation_digest":"sha256:db3a4484feed84a4b3178c19685da7d656e54636ec73822eae8c887ee614d2dc","observation_id":"cac8240e-ec80-484e-b901-5047de209b66","resolution":{"observed_at":"2026-07-02T17:37:13.993988Z","resolver_source":"arxiv_id","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":"2026-07-14T17:20:37.434528+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T17:20:37.434528+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-07-12T06:15:46.742755Z","title":"arXiv preprint arXiv:2009.10982 , year=","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.02901","last_updated":"2026-07-03T02:54:59Z","snapshot_observed_at":"2026-08-05T03:20:44.612421Z","submitted_at":"2026-07-03T02:54:59Z","title":"Proximal Mediation Analysis with Unmeasured Treatment-Induced Confounding","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-07-12T06:15:46.742755Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2607.02901"},"observation_digest":"sha256:b9ae0f9f9fc425cbc06f8b93ce7e2f4a0c45e887e336ffd0d2f16619852dec28","observation_id":"82609df9-423e-4873-ac89-76a1207d541b","resolution":{"observed_at":"2026-07-12T06:15:46.742755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.10982","snapshot_observed_at":"2026-07-14T08:15:31.506969Z","title":"arXiv preprint arXiv:2009.10982 , year =","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.10926","last_updated":"2026-07-12T21:23:13Z","snapshot_observed_at":"2026-07-16T23:19:06.127168Z","submitted_at":"2026-07-12T21:23:13Z","title":"The Spectral Structure of Latent Treatment Effects","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-07-14T08:15:31.506969Z"},"links":{"cited_paper":"/paper/2009.10982","citing_paper":"/paper/2607.10926"},"observation_digest":"sha256:61507bed657e5a2b818990a91aeb49d116673aac164e22b17fc5a93bf590ec0e","observation_id":"4e6039da-585b-4bdd-84b9-2f0b899e1596","resolution":{"observed_at":"2026-07-14T08:15:31.506969Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2009.10982/citation-record","integrity":"/paper/2009.10982/integrity","json":"/paper/2009.10982/citation-record.json","paper":"/paper/2009.10982"},"outbound":[],"paper":{"arxiv_id":"2009.10982","last_updated":"2020-09-23T07:46:53Z","latest_version":1,"primary_category":"stat.ME","snapshot_observed_at":"2026-08-06T05:37:57.951987Z","submitted_at":"2020-09-23T07:46:53Z","title":"An Introduction to Proximal Causal Learning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2009.10982."}