{"as_of":"2026-08-19T06:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d4d24f1341c783b52a7a5cd0d451e8ec4e9f76eee7eeea291cc2b5fe8d5944db","coverage":[{"denominator":75,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":75,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T04:29:15.336891Z","state":"measured"},{"denominator":76,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":76,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-12T03:23:53.494722Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-12T03:26:19.701167Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"cited_work":{"arxiv_id":"2505.01145","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.01145","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Svensson, E","venue":null,"work_id":"86220120-a10f-4cd4-85a2-36b906413ec5","year":2025},"citing_paper":{"arxiv_id":"2605.10533","last_updated":"2026-05-11T13:19:33Z","snapshot_observed_at":"2026-08-17T23:58:12.250810Z","submitted_at":"2026-05-11T13:19:33Z","title":"ConfoundingSHAP: Quantifying confounding strength in causal inference","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-12T03:23:53.494722Z"},"links":{"cited_paper":"/paper/2505.01145","citing_paper":"/paper/2605.10533"},"observation_digest":"sha256:868ca05e9a618ff3cac134b0db0c402744026202a25df9583c8f1ab686dba7dd","observation_id":"07b47c31-b381-4088-a621-0c366f5a6abd","resolution":{"observed_at":"2026-05-12T03:26:19.703019Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.01145/citation-record","integrity":"/paper/2505.01145/integrity","json":"/paper/2505.01145/citation-record.json","paper":"/paper/2505.01145"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T04:29:14.826859Z","title":"DigitalFinance 2021;3:99–148","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.826859Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:5dd154f6f8ac2e19270bc29e0db2ad330ddebc71a88ecf0126301862c32e326b","observation_id":"75ebe64f-aac8-45b9-a377-a76666724a0d","resolution":{"observed_at":"2026-08-16T04:29:14.826859Z","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":"2026-08-16T04:29:16.846014Z","title":"ProceedingsofMachineLearning Research2017: 1–13","venue":null,"work_id":"b1748759-a2ae-460b-bcfe-6237f5a548e6","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.833413Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:0c1d27765bad2cbf97038c3f6ddbdca2384f2c0f9351fd7da5b563215300021c","observation_id":"bad218dc-f6e6-4f79-9c93-a4f0cd17a43d","resolution":{"observed_at":"2026-08-16T04:29:16.849699Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.834107Z","title":"Towards optimal doubly robust estimation of heterogeneous causal effects.Electronic Journal of Statistics 2023; 17(2): 3008–3049","venue":null,"work_id":"7ce3cb80-2d60-4979-8ca9-341f2e4ac36b","year":2023},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.842783Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:309e95474db661d27c5ffac2632301a651c1fc6cd8838cf16bfdb11a5479760f","observation_id":"bff9d2ee-c7e4-4aa6-a3fe-52e1fcaddec8","resolution":{"observed_at":"2026-08-16T04:29:16.837975Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.822405Z","title":"Subgroup identification in clinical trials: an overview of available methods and their implementations with R.Annals of translational medicine2018; 6(7)","venue":null,"work_id":"9c1b6308-1cfe-4223-9ff2-1ea1066e1cfe","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.868123Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:cc10c8222d48878ed51f31a679b446039d0078841d59d4958ddd047cad8ad39f","observation_id":"af181ce5-66f5-46cb-9f75-2a6dc3ba1aa5","resolution":{"observed_at":"2026-08-16T04:29:16.826239Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:14.874104Z","title":"Modern approaches for evaluating treatment effect heterogeneity from clinical trials and observational data.Statistics In Medicine2024; 43(22): 4388-4436","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.874104Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:eac2da77b8c312bdc13a10b326e0e398a8677a88775fc6f48574e5958f37a991","observation_id":"24670211-3202-4cf2-932c-c2d5c6396566","resolution":{"observed_at":"2026-08-16T04:29:14.874104Z","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":"2026-08-16T04:29:14.882465Z","title":"Biometrics2017; 73: 1199-1209","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.882465Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:3600d945214389a519166325eff4f37ae580ec395f75d8674e2dc281f59b14c3","observation_id":"a7be1206-b853-4600-9f1d-68b5fb8d33ac","resolution":{"observed_at":"2026-08-16T04:29:14.882465Z","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":"2026-08-16T04:29:14.895059Z","title":"Metalearners for estimating heterogeneous treatment effects using machine learning","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.895059Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:6830b57bb7b33346e50adf8b1cb4a7313aaeb6ae92c6fa823173a80ed1b4921d","observation_id":"094daae8-fccc-4b5a-8fbe-5a539a1f37d0","resolution":{"observed_at":"2026-08-16T04:29:14.895059Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2007.02852","last_updated":"2020-08-26T17:34:29Z","snapshot_observed_at":"2026-08-18T21:32:05.275672Z","submitted_at":"2020-07-06T16:09:00Z","title":"Cross-Fitting and Averaging for Machine Learning Estimation of Heterogeneous Treatment Effects","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.02852","snapshot_observed_at":"2026-08-16T04:29:14.901794Z","title":"Cross-fitting and averaging for machine learning estimation of heterogeneous treatment effects","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.901794Z"},"links":{"cited_paper":"/paper/2007.02852","citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:313726ade88ab3e5e6ff65492702df0553dde23a4c553e7b4fb4ebc85dcfb49a","observation_id":"f66db7ce-b08f-4cba-a3a1-75f628b59e7b","resolution":{"observed_at":"2026-08-16T04:29:14.901794Z","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":"2026-08-16T04:29:16.809794Z","title":"Subgroup identification using the personalized package.Journal of Statistical Software2021; 98(5): 1-–60","venue":null,"work_id":"66664144-4e51-4b15-97aa-eca0f2bce51b","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.908231Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:1f5b729aea76807f303a9d1e0efe281a74372d4bf4b9ea178e680a3037eb4055","observation_id":"374ce126-0fe4-4adf-89b1-1c818ef7613a","resolution":{"observed_at":"2026-08-16T04:29:16.813428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.798485Z","title":"ObservationalStudies 2016;5(2):37–51","venue":null,"work_id":"0e0db9d5-ad1d-4e79-abfa-a9296c35ff5c","year":2016},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.917822Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:a680fae86719ed2e8859054887a20f5e01169c4230bfcba63a1ceb5129de0760","observation_id":"371d080b-7673-4253-8403-552ba7553c01","resolution":{"observed_at":"2026-08-16T04:29:16.802250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.782104Z","title":"Some methods for heterogeneous treatment effect estimation in high dimensions.Statistics in Medicine2018; 37(11): 1767–1787","venue":null,"work_id":"eb95073e-5825-4f61-9b09-0d7b624e3b3a","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.927745Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:27629f2fb3c55711254a00c096908e18f37e664d6d27ed63d5326ff73a2521bf","observation_id":"c1a161d8-18a2-4424-95a9-7d3eafc603a8","resolution":{"observed_at":"2026-08-16T04:29:16.786454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.765068Z","title":"CRAN brf package: Causal Inference for a Binary Treatment and Continuous Outcome using Bayesian Causal Forests","venue":null,"work_id":"690c4747-922e-4a8d-80e8-7fe5e288e114","year":2022},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.934553Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:786336f8d307363b59f9277b5d91234f7c2682289a8c2fd370092eacedfbb82e","observation_id":"14aa20c7-1f10-4416-a5f5-49391d70486b","resolution":{"observed_at":"2026-08-16T04:29:16.770096Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:14.940192Z","title":"Predictive biomarker identification for biopharmaceutical development.Statistics in Biopharmaceutical Research2021; 13(2): 239–247","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.940192Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:678ebc6f11fbfc5861c7eb162e7498f9a5262553f480e6b15b9872703807685b","observation_id":"25bf00c4-7e1c-43ec-b0be-8f1f0ad91a22","resolution":{"observed_at":"2026-08-16T04:29:14.940192Z","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":"10.1186/s12890-019-0889-4","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T04:29:15.574041Z","title":null,"venue":null,"work_id":"448bdf27-706b-4518-a81c-7470fa788f1b","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.946350Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:c7b378f0d7e22bd826b23fc0d5523381a57cc099780f25df8d1cd0225486824e","observation_id":"e47043f2-f15c-495c-8b92-ab3b2a8830b0","resolution":{"observed_at":"2026-08-16T04:29:15.578736Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/widm.1326","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T04:29:15.552273Z","title":"DataMining Knowl Discov2019; 9(5)","venue":null,"work_id":"e0c91f71-e4b4-46c1-aa2f-e57cae87a36f","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.952303Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:3c68c1c96bab9e983bcb52c74f526fdcebb44c51af39915daf1785128ca963db","observation_id":"ffbd37b7-eb92-4fa1-bbfd-9adc4a576738","resolution":{"observed_at":"2026-08-16T04:29:15.558873Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.750620Z","title":"35thConferenceonNeuralInformationProcessingSystems(NeurIPS), Track on Datasets and Benchmarks2021","venue":null,"work_id":"8725b0c4-f6cd-4698-8d34-156839cef8eb","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.958343Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:a7ec6d9e26b60ac3c160192ae4d551cb80da9592770c243b377c4c6c34b1bd2e","observation_id":"121feaa0-acb2-4305-bfa5-3540e92c3d69","resolution":{"observed_at":"2026-08-16T04:29:16.755081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/pst.2463","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T11:08:47.750906Z","title":"WATCH: A Workflow to Assess Treatment Effect Heterogeneity in Drug Development for Clinical Trial Sponsors.Pharmaceutical Statistics2025; 24(2): e2463","venue":"Pharmaceutical Statistics","work_id":"d03a44d8-7d94-4fb1-9bff-f46022c277fa","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.964534Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:ac3cbf1cf694939d0ca1eebecac53a9706722748abf2dbcddac4744b869813a0","observation_id":"edbb804c-f8c4-448b-b802-e384fd32d981","resolution":{"observed_at":"2026-08-16T04:29:15.533987Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1093/bioinformatics/bty515","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T04:29:15.507275Z","title":"Distinguishing prognostic and predictive biomarkers: an information theoretic approach.Bioinformatics 2018; 34(23)","venue":null,"work_id":"b9f90bf2-f878-44b5-8df5-0bb2b0c4357d","year":2018},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.970931Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:9189152ad617ed48f406a6e27a30b23a5612b13d7fc8bba0bf93dd04a9e77e39","observation_id":"77befcd9-6815-4b7d-923e-fb53fbb1d81e","resolution":{"observed_at":"2026-08-16T04:29:15.513575Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.737134Z","title":"Springer New York, NY","venue":null,"work_id":"a4cf5e7f-512b-44c7-8bba-cb405d410de3","year":2009},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.978405Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:c382108415d3fca7ca53651e056ac73e63846f51c9f63269144e2e0049741051","observation_id":"992e0885-c483-4213-ab20-85a2d422d7a1","resolution":{"observed_at":"2026-08-16T04:29:16.741908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.720817Z","title":"A unified approach to interpreting model predictions..Advances in Neural Information Processing Systems2017; 30","venue":null,"work_id":"00d184a5-34e2-4d9b-9968-b7ae3fe0b3cc","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.987778Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:0696cef6fd12bae7d4a3c620e1f4075229124280df4dba2965895ee2bd7f6cbb","observation_id":"ddb34bbf-6211-4e0e-9bc1-8406c36190db","resolution":{"observed_at":"2026-08-16T04:29:16.724434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.02467","last_updated":"2024-03-04T20:28:28Z","snapshot_observed_at":"2026-08-16T14:12:53.670937Z","submitted_at":"2024-03-04T20:28:28Z","title":"Applied Causal Inference Powered by ML and AI","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.02467","snapshot_observed_at":"2026-08-16T04:29:14.995233Z","title":"Applied Causal Inference Powered by ML and AI.arxiv (book manuscript)2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:14.995233Z"},"links":{"cited_paper":"/paper/2403.02467","citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:b7da912c7005e073e3d5c77019f33427b3e56f162aa62c63335f301f7d8cd56e","observation_id":"70f73912-42a5-4ce2-8a6c-1d52a2c5dd40","resolution":{"observed_at":"2026-08-16T04:29:14.995233Z","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":"2026-08-16T04:29:16.708482Z","title":"In: International Committee on Computational Linguistics","venue":null,"work_id":"9e4eb2b8-a80b-48ac-b769-d7bb64ab78dc","year":2022},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.002346Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:26db0b250370fb3f6a2b52b6a4c7f3dbfcd492075ee27c10b6c893055cdf8978","observation_id":"22ad1dee-adbf-4be8-8256-4b5a02408143","resolution":{"observed_at":"2026-08-16T04:29:16.711945Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.01625","last_updated":"2020-11-03T11:11:36Z","snapshot_observed_at":"2026-08-16T19:08:28.380839Z","submitted_at":"2020-11-03T11:11:36Z","title":"Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.01625","snapshot_observed_at":"2026-08-16T04:29:15.010508Z","title":"Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.010508Z"},"links":{"cited_paper":"/paper/2011.01625","citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:c1dd2bb6cb5843bc663bfdab77224f938c7a8f880f106a60d3b8b71a955f6c34","observation_id":"a3aa797b-ad48-448e-b974-760482c8845e","resolution":{"observed_at":"2026-08-16T04:29:15.010508Z","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":"2026-08-16T04:29:15.017608Z","title":"Variable importance measures for heterogeneous causal effects.arXiv preprint arXiv:2204.060302022","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.017608Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:6bd1ea23e687320265a61c7cb2cc819199eb702cc488f9d4aafa3d29147cb747","observation_id":"8d08de3d-1806-47c2-b2bf-7188083fc09a","resolution":{"observed_at":"2026-08-16T04:29:15.017608Z","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":"2026-08-16T04:29:16.695579Z","title":"Subgroup identification from randomized clinical trial data.Statistics in Medicine2011; 30(24): 2867–2880","venue":null,"work_id":"32fc9e8e-8719-4f8f-a24f-3c062feaefb5","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.024102Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:d6b771042cfbf2ffe3ceb9bf965405a3ebd724186f79ca3c9ecabb8c9d52bdc5","observation_id":"98fd0d29-9710-48d1-8079-f85ffc4e3f18","resolution":{"observed_at":"2026-08-16T04:29:16.700296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.683030Z","title":null,"venue":null,"work_id":"d8396f46-71c8-4b5d-9d98-2875527a2963","year":2019},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.031233Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:4e3db71736c14e956befe0e56987c0832e104199d180d8c979bb98ce9b4b0dcc","observation_id":"37cf0527-476c-4423-a70d-cd102f99c43c","resolution":{"observed_at":"2026-08-16T04:29:16.686972Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.669532Z","title":"Bagging predictors.Machine learning1996; 24(2): 123–140","venue":null,"work_id":"fa28bc2c-f654-4449-a41b-f83876be4827","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.036813Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:7aba4f453195313389dec2fe13336db402632802d93e3d7d06275c68e283e502","observation_id":"b4654e9d-7829-436c-a258-3ce8f5719974","resolution":{"observed_at":"2026-08-16T04:29:16.674458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:15.044379Z","title":"TheAnnalsofAppliedStatistics 2010; 4(1): 266 – 298","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.044379Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:f8bf167ae8d656dc6b80009c1a4ca2540a4c4ef816e92404deecb44e49394aa7","observation_id":"4ef2c25f-6372-4186-a423-5c92b546be24","resolution":{"observed_at":"2026-08-16T04:29:15.044379Z","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":"2026-08-16T04:29:16.654097Z","title":"Classification and regression trees.Wiley interdisciplinary reviews: data mining and knowledge discovery2011; 1(1): 14–23","venue":null,"work_id":"d4920461-c88c-407a-b5ea-0eda0431a702","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.050764Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:f5750e93587ca585006445d87692e5551f80d430a561e50cf87e1f491784a488","observation_id":"f4e5a9f1-f59a-45ee-8beb-7b72c1fb774d","resolution":{"observed_at":"2026-08-16T04:29:16.658860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.640459Z","title":"Estimating causal effects of treatments in randomized and nonrandomized studies.Journal of Educational Psychology1974; 66(5): 688–701","venue":null,"work_id":"13df16d5-5823-40e5-88bd-aabc6fa33413","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.056017Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:8a47d848f03ddc29a712b97f0ab7feac0b40b9e517a6c5047cc9923a953b2df7","observation_id":"f075373e-afc4-4b3e-95de-b8601d1744dc","resolution":{"observed_at":"2026-08-16T04:29:16.644613Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.627466Z","title":"Generic machine learning inference on heterogeneous treatment effects in randomized experiments, with an application to immunization in India.NBER Working Paper2018(No","venue":null,"work_id":"c971fa1f-3ce3-4aeb-ae16-87e071414040","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.062859Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:048f367e330190d97caed4db79e1811015fa49a3af91d5076c849806e3349c8b","observation_id":"333d0676-d6c5-4aca-862d-d62ccf6e417a","resolution":{"observed_at":"2026-08-16T04:29:16.632181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:15.071356Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.071356Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:e5ef7d05bf83e89685c41b1eadd4449e5fb45fad07e6d76007488835614e85b8","observation_id":"8473be29-b1e4-4d81-bcc5-f682c3d6460b","resolution":{"observed_at":"2026-08-16T04:29:15.071356Z","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":"2026-08-16T04:29:16.612697Z","title":"WIREsData Mining and Knowledge Discovery2019; 9(5): e1326","venue":null,"work_id":"aaf48287-42ad-4981-9925-a198ac97bd4e","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.078814Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:9bb9f8027bb5f9d61ee0f9cc7ed489b5e4139e930fa188040f337aba7c4ece1e","observation_id":"1844f96f-402f-4754-9409-1494214e8268","resolution":{"observed_at":"2026-08-16T04:29:16.617166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.600779Z","title":"Validating Causal Inference Models via Influence Functions","venue":null,"work_id":"103655ee-34b8-4706-a993-7d3bd26c6638","year":2019},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.084995Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:955fa448bb694ed8b85e000b5d5c1ef976c2085974650bc725e96c69668c4933","observation_id":"e05e6d22-4332-4fd7-b28e-af87570948be","resolution":{"observed_at":"2026-08-16T04:29:16.604551Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.586475Z","title":"StatisticsinBiopharmaceuticalResearch 2015; 7(3): 214–229","venue":null,"work_id":"b22835c5-3592-42ce-919d-2410855393cd","year":2015},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.093669Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:0a862b7d3e1f275c590a414d186e11df2abd5dd335d02c39519f0cf061fbcc2c","observation_id":"87bbd278-43e0-41b6-9bb9-42c58516c8e6","resolution":{"observed_at":"2026-08-16T04:29:16.592558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.570867Z","title":"Generalized random forests.The Annals of Statistics2019; 47(2): 1148–1178","venue":null,"work_id":"651876c2-ceaf-42db-bc44-bf529968bd50","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.100632Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:ba32b0b0514dc45d8da82a2bc63f0c5881df0e641e14c2e729b7f17cf7dc5c48","observation_id":"d90380fa-0a6c-4999-aa04-f77069ff41a5","resolution":{"observed_at":"2026-08-16T04:29:16.575746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:15.107996Z","title":"doi: https://doi.org/10.1214/19-BA1195","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.107996Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:1123f4e63cd87d22d1e9128d4ef40e7a12f89a93681c7598ac4b6d8cc3c401f0","observation_id":"af58c9af-24ca-493b-a5af-27b7fb7eeb78","resolution":{"observed_at":"2026-08-16T04:29:15.107996Z","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":"2026-08-16T04:29:16.557654Z","title":"On discovering treatment-effect modifiers using Virtual Twins and Causal Forest ML in the presence of prognostic biomarkers","venue":null,"work_id":"e45a74ce-bd14-41dc-82e7-89d5dbf3c4da","year":2021},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.114274Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:aae8759b4d2d1988a472eca15d75e66576ea25ab3f1e310b78afe103224d444e","observation_id":"33efef2a-d4c7-466c-a1b4-3f864e3c7137","resolution":{"observed_at":"2026-08-16T04:29:16.561985Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.542782Z","title":"rlearner: Quasi-Oracle Estimation of Heterogeneous Treatment Effects","venue":null,"work_id":"67866c98-3e7d-42fa-86df-789f7e57a4b0","year":2023},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.123047Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:438ba3fe79605ba0c48017cd4b1ba238c056b6bda35d68a0a534cdb210b4e51c","observation_id":"2c04a615-60fa-4857-aaee-a6c972949c41","resolution":{"observed_at":"2026-08-16T04:29:16.548383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.527980Z","title":"Root- N-Consistent Semiparametric Regression.Econometrica1988; 56(4): 931–54","venue":null,"work_id":"c88b0b62-c485-4bc2-bd8e-4b81a4af1a4a","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.128818Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:a51ed56159817d766cf7a4e3fa9f86519470f9694ff8cb721429951561f61aff","observation_id":"6abfeb3f-a938-453f-8dfa-e34028cbbccd","resolution":{"observed_at":"2026-08-16T04:29:16.532865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.511803Z","title":"Recursive partitioning for heterogeneous causal effects.Proceedings of the National Academy of Sciences 2016; 113(27): 7353–7360","venue":null,"work_id":"831aee1a-0bec-4769-b066-1f7ec2c8288d","year":2016},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.133811Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:cc6848012806a3528d32f69488f1e1b215857cc3d7ff39f7d6546375689aeb2d","observation_id":"726bd69f-0b3a-4e66-89fe-e4eb56cd18ad","resolution":{"observed_at":"2026-08-16T04:29:16.517912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.492940Z","title":"A simple method for estimating interactions between a treatment and a large number of covariates.Journal of the American Statistical Association2014; 109(508): 1517–1532","venue":null,"work_id":"9778f864-5427-47b8-84df-5b53a01597d6","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.138545Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:7339f51c630e44c1521051117dece7b9feffb2482ac2c1ec1d64a431e1d55893","observation_id":"4bb7308b-763d-4eec-942f-8cc5c5f7d627","resolution":{"observed_at":"2026-08-16T04:29:16.503560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.473566Z","title":"M.Interpretable Machine Learning: A Guide for Making Black Box Models Explainable","venue":null,"work_id":"acafce0e-c05d-4c2d-8ed1-ad0e719b80f9","year":2019},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.142292Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:cbd966d19f2876dc5ad33e3e017854bbae1b9ab7bb13f98970f4a24ba3e06b1f","observation_id":"f926fb50-78da-4280-8870-c5b0795effac","resolution":{"observed_at":"2026-08-16T04:29:16.478800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.460357Z","title":null,"venue":null,"work_id":"3a2adaf2-c909-49da-955c-e7eb29209f3d","year":2020},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.145952Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:6aaf083a20e75c99bdc8732af98c290d4334e46796b780c4512d0e64a6f0b64f","observation_id":"12543eb3-54c8-4e84-9cac-bb7fbca08f2c","resolution":{"observed_at":"2026-08-16T04:29:16.464153Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.447321Z","title":"Whyshoulditrustyou?","venue":null,"work_id":"0e6f412e-b238-42f7-af9f-fb8d52f34e15","year":2016},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.151422Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:a748cf4aabaa73c7d71470808d0d8bd52788066d10bd3cb745cb01361d8ad842","observation_id":"70290938-2182-4b1a-99e6-16d044681f41","resolution":{"observed_at":"2026-08-16T04:29:16.451355Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.434703Z","title":"Deep inside convolutional networks: visualising image classification models and saliency maps","venue":null,"work_id":"6097e90a-0ebc-4708-8dc7-6adc569b8916","year":2014},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.156068Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:f95f22e7384785ba6130fd17b9cf062be736d0fae27abec85cb89013df0071e2","observation_id":"0a88e783-93ca-402a-aa0d-2644ec477ccf","resolution":{"observed_at":"2026-08-16T04:29:16.439148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.421497Z","title":"2017: 3145–3153","venue":null,"work_id":"310feec7-e64e-4ebe-bc72-1847ca5dafc6","year":2017},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.160332Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:b8ece055679095aceb86544545e22fca8b545e8b8556f3355b0a2b89ac974afc","observation_id":"d339b1ef-6d66-4e54-9bdf-aaca84333c30","resolution":{"observed_at":"2026-08-16T04:29:16.425642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.409191Z","title":"Grad-cam: Visual explanations from deep networks via gradient-based localization","venue":null,"work_id":"7b402f09-7718-4069-ba31-13faf9998cda","year":2017},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.165460Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:610269d214497d2d604f846a324cd981f4f8d2d49f83cf481d11c09ad5be9c70","observation_id":"31d93383-789b-4180-aacb-14ec94bd7056","resolution":{"observed_at":"2026-08-16T04:29:16.413310Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.03825","last_updated":"2017-06-12T19:53:30Z","snapshot_observed_at":"2026-08-14T20:54:30.978618Z","submitted_at":"2017-06-12T19:53:30Z","title":"SmoothGrad: removing noise by adding noise","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.03825","snapshot_observed_at":"2026-08-16T04:29:15.175543Z","title":"Smoothgrad: removing noise by adding noise.arXiv preprint arXiv:1706.038252017","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.175543Z"},"links":{"cited_paper":"/paper/1706.03825","citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:81ce6c500d1f9f1ad8b30478fefa2f79bd6948f511918bfd0e55dab1cfe13059","observation_id":"42a0623b-5b54-4666-8803-fb22df33d218","resolution":{"observed_at":"2026-08-16T04:29:15.175543Z","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":"2026-08-16T04:29:16.395493Z","title":"A Guide for Making Black Box Models Explainable","venue":null,"work_id":"7723dcb1-26ab-4156-8cb8-3d68a1370088","year":2024},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.185424Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:eb8d472833da85bef7ae10cf30a486064f9b18f9df1b22fb38f391a6352f1d49","observation_id":"2a881ebf-f433-4530-93cb-58c4b54cc87d","resolution":{"observed_at":"2026-08-16T04:29:16.399564Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.381270Z","title":"A Value for n-Person Games: 307–318; Princeton: Princeton University Press","venue":null,"work_id":"52fed957-1333-485b-9a5b-1e8afd0bb1ac","year":1953},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.192300Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:97a082e074b872a1d76f5fc10b8926f3e28ff721e65c49f5ccb1f4ab6d447ecb","observation_id":"232ea52c-e60d-4925-89cf-223bbb1e9f32","resolution":{"observed_at":"2026-08-16T04:29:16.385380Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.08474","last_updated":"2020-02-07T17:43:11Z","snapshot_observed_at":"2026-08-17T18:07:02.436079Z","submitted_at":"2019-08-22T16:13:10Z","title":"The many Shapley values for model explanation","version":2},"cited_work":{"arxiv_id":"1908.08474","doi":null,"metadata_source":"pith","pith_arxiv_id":"1908.08474","snapshot_observed_at":"2026-08-16T04:29:15.874517Z","title":"The many Shapley values for model explanation","venue":"cs.AI","work_id":"f537b2aa-6876-4e30-ba7c-42f74d624eb7","year":2019},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.197345Z"},"links":{"cited_paper":"/paper/1908.08474","citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:4d2f8cf1996fa96ee3999892de15057fe6df8527d70a40a5aabb3771fb93fa11","observation_id":"01160bf8-a319-4390-a9c3-fb9123f752d8","resolution":{"observed_at":"2026-08-16T04:29:15.878968Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.366548Z","title":"Greedy function approximation: a gradient boosting machine.Annals of statistics2001: 1189–1232","venue":null,"work_id":"fcd48f04-b82f-4b95-b289-947a0c800231","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.211849Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:c637ddf0e3c458d5b015e1d30b4053ad7dc4bf503e3e7de84125db5b7ec7ea90","observation_id":"81f86397-9bd8-449d-8dfa-f6a51bcc7c07","resolution":{"observed_at":"2026-08-16T04:29:16.371421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.350044Z","title":"Nature machine intelligence2020; 2(1): 56–67","venue":null,"work_id":"8eef4bc0-94ea-4efa-a86d-2dc3c97af01b","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.215513Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:b092a6883707f9e9d6250afd5d4304095fe6528a92272d60eab04453a6b356dc","observation_id":"9e06c110-a199-49b2-96d2-404322454dab","resolution":{"observed_at":"2026-08-16T04:29:16.356352Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:15.219518Z","title":"Improving the Sampling Strategy in KernelSHAP.arXiv preprint arXiv:2410.048832024","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.219518Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:55f40b69ef907de4713f05915d6b3ea006a9a6432d6e78b23819cf0a71759c81","observation_id":"01323ecf-f5f2-46d4-881a-9c91acb24918","resolution":{"observed_at":"2026-08-16T04:29:15.219518Z","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":"2026-08-16T04:29:16.336384Z","title":"Algorithms to estimate Shapley value feature attributions.Nature Machine Intelligence2023; 5(6): 590–601","venue":null,"work_id":"e445078f-0b0c-4921-9930-df920e782185","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.223892Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:7c5e165b45fb428ca75e79038032de825e752940c1202e1a306cc3516a06d543","observation_id":"c692d266-a72c-4059-9b21-39aa28d0c458","resolution":{"observed_at":"2026-08-16T04:29:16.340941Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.324416Z","title":null,"venue":null,"work_id":"520909b6-817a-4a19-8da3-6ca14c9458f3","year":2024},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.228251Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:c8d10da2a1f31f619385e3e64ba0e22e1ee4276c78ca280095c1ec560786f942","observation_id":"c4beef9a-c7cf-483c-a65b-3308c3b0eef2","resolution":{"observed_at":"2026-08-16T04:29:16.328268Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.313083Z","title":"CRAN; CRAN: 2021","venue":null,"work_id":"84c896fe-0714-45e4-b26a-2f4e7225b667","year":2021},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.232708Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:21023224074d8ee81c83fc38b0079c88389485fc026b696b1f506f769bc39b3d","observation_id":"e7907e94-b419-4f57-a018-de2a90a3d3c8","resolution":{"observed_at":"2026-08-16T04:29:16.316527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.21105/joss.02027","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T04:29:15.441271Z","title":"shapr: An R-package for explaining machine learning models with dependence-aware Shapley values.Journal of Open Source Software2019; 5(46): 2027","venue":null,"work_id":"a6ae6928-782e-43f6-af1c-4a089a47d195","year":2027},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.236919Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:c91794c29fbcc700aaa7fb0925e8de3ee091acab29edfaa03bba6ca462b9fd8a","observation_id":"82d95ce9-fbe9-4f55-89bb-389d22ae446c","resolution":{"observed_at":"2026-08-16T04:29:15.446325Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.300726Z","title":null,"venue":null,"work_id":"3bbef31c-d4ae-48a7-97a0-ed5fa8722989","year":2024},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.244055Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:6cbbd42faef243ca7cb721010b6c550eea2a17f4a02cc5088d9c851c363f22bc","observation_id":"cef528af-8ec6-4e57-8b8e-eaa1c2a3a547","resolution":{"observed_at":"2026-08-16T04:29:16.304629Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.279094Z","title":"Model-agnostic interpretability with shapley values","venue":null,"work_id":"d692f768-1b81-4c71-871c-e9dfa3272db5","year":2019},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.248135Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:70116850824246eaeb8bee92e5c09c517f9279788ea771a7175084c54f1ae71d","observation_id":"4955a500-79ec-4e37-815b-9cfc38ec6ef6","resolution":{"observed_at":"2026-08-16T04:29:16.286928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:15.252523Z","title":"SHAP-Based Explanation Methods: A Review for NLP Inter- pretability","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.252523Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:58b826e8f03cfb4b4e07171b07876da6d98ebcf8324b14fde934cd65ad62ac73","observation_id":"a7603091-ff5b-4eb4-906a-a6c341cb3933","resolution":{"observed_at":"2026-08-16T04:29:15.252523Z","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":"2026-08-16T04:29:15.258155Z","title":"Tabular data: Deep learning is not all you need.Information Fusion2022; 81: 84-90","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.258155Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:9438ea1fe75529763261ada597495fee061c7f0756c96a1852b129569215a757","observation_id":"3f4f41ea-711e-4074-89b4-ec4f99980204","resolution":{"observed_at":"2026-08-16T04:29:15.258155Z","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":"2026-08-16T04:29:16.254086Z","title":"Why do tree-based models still outperform deep learning on typical tabular data?","venue":null,"work_id":"f748ac3b-f9f2-4c94-b458-866479a64fe3","year":2022},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.269065Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:e107188d8f72d338123938b68684832466c5bdac28c4a9b08a98c6b9c7d64a68","observation_id":"c50f9355-87ed-443a-9883-dcb62e5894a1","resolution":{"observed_at":"2026-08-16T04:29:16.266746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.234459Z","title":"CRAN; CRAN: 2023","venue":null,"work_id":"7090efc0-1be2-4291-afa6-10dd2dc9d6f3","year":2023},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.278640Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:8a3610b25a7ef9945868626274d1a5c1208ec0ad43116a7f9c11e84718cc2ca0","observation_id":"2cdb654d-4338-45ab-8e13-4727616a9216","resolution":{"observed_at":"2026-08-16T04:29:16.239146Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.222310Z","title":"Classification and Regression by randomForest.R News2002; 2(3): 18-22","venue":null,"work_id":"aa4cd3b2-1784-4b1c-b192-b416db51e151","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.283656Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:e80603df6f5d36398f76d26d4dfc441f7f14dd71e101b5cbcd202884de4956da","observation_id":"25c9601d-cd4d-489e-8806-21845e8453f0","resolution":{"observed_at":"2026-08-16T04:29:16.225959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.209686Z","title":"XGBoost: A Scalable Tree Boosting System","venue":null,"work_id":"345c2173-5b55-4149-9c35-c8914222cfc0","year":2016},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.289546Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:d460ad132921dea708aa7ec530956b5f6e84789d5af9d4831cfdbd1507b22e20","observation_id":"436ab090-4b4b-436d-a843-bb6ce8e9cb36","resolution":{"observed_at":"2026-08-16T04:29:16.214409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1177/17407745231174544","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T04:29:15.405101Z","title":"Overview of modern approaches for identifying and evaluating heterogeneous treatment effects from clinical data.Clinical Trials2023; 20(4)","venue":null,"work_id":"a875e494-afa4-49c2-a48a-c2e301b92d69","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.295898Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:403f1cc026764a60b1e179dc764cd88096fcf1907310be6be2ed7e396434e307","observation_id":"41f62dce-57e8-4115-a771-0f270872ae22","resolution":{"observed_at":"2026-08-16T04:29:15.412890Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/sim.7660","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T04:29:15.379003Z","title":"Random Forests of Interaction Trees for Estimating Individualized Treatment Effects in Randomized Trials.Statistics in Medicine2017; 37","venue":null,"work_id":"3454be28-0fb6-46b4-b51e-f7c4c4df7e08","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.300551Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:fc57a30366bfcfa6b30619389a93b6d34ab5a73694ef228ede0eb4fff3a6ee23","observation_id":"8bb32b3b-84fa-4591-8726-96cb2e568d88","resolution":{"observed_at":"2026-08-16T04:29:15.386380Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"8029.42186","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T04:29:15.725122Z","title":"Acupuncture for chronic headache in primary care: large, pragmatic, randomised trial","venue":null,"work_id":"61899c82-0525-4e4f-8cf1-a09d690a9b95","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.308621Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:b7d15f2f859dc4c78562d48de24b62e0be7cd02d549dc94212de5982c5defdc7","observation_id":"96b2bced-7beb-4f06-87c8-0907c0408d30","resolution":{"observed_at":"2026-08-16T04:29:15.732691Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.191104Z","title":"Model-based recursive partitioning for subgroup analyses.The International Journal of Biostatistics2016; 12(1): 45–63","venue":null,"work_id":"7c270653-b22f-41b0-b8df-cf0d99eaa76b","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.312769Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:6f791f3252a6a0d12985e93a89db23f06d98639b7c67b63a8132711c4d79d3a0","observation_id":"ed7f8bac-972d-414e-905d-99381dc99c75","resolution":{"observed_at":"2026-08-16T04:29:16.199774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.161976Z","title":"Distilling heterogeneous treatment effects: Stable subgroup estimation in causal inference.arxiv 2025","venue":null,"work_id":"8d33c912-f31f-472d-a4b4-729be87806b4","year":2025},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.319255Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:75538feffb2ee19fdabc9c8a58017da7eb4ce4be5a3567fe22e15976ea4082f8","observation_id":"57b0e9c4-00c0-40a6-a797-b8811958effb","resolution":{"observed_at":"2026-08-16T04:29:16.167126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.146886Z","title":"Experimental evaluation of individualized treatment rules.Journal of the American Statistical Association 2021; 0(0): 1-15","venue":null,"work_id":"66cf8f7f-542a-4894-8d15-036260368f91","year":2021},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.325379Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:f340041136e763454b3f0a555fb5a15f357568f11bbf5f88ac48b35091ac2afe","observation_id":"06445499-a8b2-41f1-bb33-b619d2d8ac2f","resolution":{"observed_at":"2026-08-16T04:29:16.150851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.133125Z","title":"LLpowershap: logistic loss-based automated Shapley values feature selection method.BMC Medical Research Methodology2024; 24(1): 247","venue":null,"work_id":"4d3246a7-d9ea-445a-8b1b-77dff7656ef3","year":null},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.332935Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:021120a4282ababcebdcc6a32bdc7ddaee67074eb470e8318e83498a663e32e6","observation_id":"038f2651-4404-4b81-9a62-37c7565e76d6","resolution":{"observed_at":"2026-08-16T04:29:16.137445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T04:29:16.116847Z","title":"In: Neural Information Processing Systems","venue":null,"work_id":"ff54c4af-d7ce-4817-8505-e4f078249ef8","year":2024},"citing_paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-16T04:29:15.336891Z"},"links":{"citing_paper":"/paper/2505.01145"},"observation_digest":"sha256:a8407862b89b6fb61fa8487e009b641c6a21f4008b5a721f6f9e0a9e09d5fd6b","observation_id":"7d403864-716d-4c53-b491-d40caa876d0d","resolution":{"observed_at":"2026-08-16T04:29:16.120609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.01145","last_updated":"2025-05-02T09:44:04Z","latest_version":1,"primary_category":"stat.ME","snapshot_observed_at":"2026-08-18T16:11:53.051871Z","submitted_at":"2025-05-02T09:44:04Z","title":"Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling"},"reference_resolution":{"displayed":75,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":20,"verified_exact":8,"verified_fuzzy":46},"total_outbound_references":75},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 1 inbound Pith citation observation for arXiv:2505.01145."}