{"as_of":"2026-08-07T08:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:441db57dd79d36d7da67f6b3c768894c176c74f22dbef107a31d19e4bda172f1","coverage":[{"denominator":36,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":36,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-09T16:26:45.951896Z","state":"measured"},{"denominator":36,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":36,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.07247/citation-record","integrity":"/paper/2607.07247/integrity","json":"/paper/2607.07247/citation-record.json","paper":"/paper/2607.07247"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T16:36:21.623813Z","title":"Riley RD, van der Windt D, Croft P, Moons KGM, editors: Oxford University Press; 2019 01 Feb 2019","venue":null,"work_id":"73db83ac-1163-41d5-b385-06279d84dc1d","year":2019},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:aee468d7560286a404f2c04f7bdb082cd06e950b8a72b439d28770b502123570","observation_id":"573ad0f6-8d6f-4e8c-93d5-3de692f7cffe","resolution":{"observed_at":"2026-07-09T16:36:21.625134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.641684Z","title":"Development and validation of a prediction model with missing predictor data: a practical approach","venue":null,"work_id":"fe500b35-eb97-4810-bddd-428cd0339ddb","year":2010},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:a2fedf47a21ed055ea60d0d3ee1f430bef85895a4a4ac4b7c5b6245eef4f0917","observation_id":"82edd6dd-938b-413a-988d-663daeeb263a","resolution":{"observed_at":"2026-07-09T16:36:21.642955Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.659062Z","title":"Combining multiple imputation with internal model validation in clinical prediction modeling: a systematic methodological review","venue":null,"work_id":"48fe1c09-0b40-4589-a36a-66be261121e4","year":2025},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:b7c1e02ce3d6e6e412b6a48f65c478fb5dcac3c75c961e48b15ee911ff40a24a","observation_id":"94c756c9-7f63-4b1d-8261-802484b9500c","resolution":{"observed_at":"2026-07-09T16:36:21.660444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.660984Z","title":"Bias arising from missing data in predictive models","venue":null,"work_id":"dc1d4e8e-869f-418c-a3e2-5e33995f14ba","year":2006},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:ff9ef0734c1d773921d335805bbb0df07855d55c8fa259f1b5d522460bfadff7","observation_id":"90328ecb-c018-40ad-aec2-df7b7f380bb2","resolution":{"observed_at":"2026-07-09T16:36:21.662215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.686688Z","title":"Missing data should be handled differently for prediction than for description or causal explanation","venue":null,"work_id":"4355e188-af67-4717-a732-93b2ef51426a","year":null},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:daad402790bfc1542d373364f1cc18e85614e75bba7c78e5434d5517fbd76738","observation_id":"7d04c200-4ad8-46f6-b4ae-bfcf2fd2b9a8","resolution":{"observed_at":"2026-07-09T16:36:21.688060Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.635798Z","title":"Uncertainty of risk estimates from clinical prediction models: rationale, challenges, and approaches","venue":null,"work_id":"57d8bdbb-0e15-4117-9042-50cec35bdf6f","year":2025},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:69da6e96236c2d6509ffac0d33454a76d5bf90644632d07b5cd54590ea687c57","observation_id":"9ca63bd2-b34b-4874-84a6-e1aee977c288","resolution":{"observed_at":"2026-07-09T16:36:21.637468Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.631949Z","title":"The performance of prognostic models depended on the choice of missing value imputation algorithm: a simulation study","venue":null,"work_id":"d9b09a13-8476-483a-b4c2-16ad341c78c6","year":2024},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:8deef03e230be42149b2615843e08be57edf0b51489da78a50fff169773217bd","observation_id":"7c331c4d-5dc1-49ac-b206-2437d849f612","resolution":{"observed_at":"2026-07-09T16:36:21.633211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.662943Z","title":"Stability of multivariable fractional polynomial models with selection of variables and transformations: a bootstrap investigation","venue":null,"work_id":"fae0820f-ad19-495c-a084-003780d77e14","year":2003},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:0a17d9885780ae6f76cca8db4ca3873f9d3534e0e5a5139fb5e2572d954792f3","observation_id":"8947f3c2-21c5-493b-a7e8-c0a0ba867675","resolution":{"observed_at":"2026-07-09T16:36:21.664479Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.665029Z","title":"On stability issues in deriving multivariable regression models","venue":null,"work_id":"38c66f88-ef66-48d6-a3b9-6ebbd97c05f9","year":2015},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:4b10c10fe7d76f79900a0daa2edf4fd11a7d682cbc61998a61b420baea77caad","observation_id":"0a47a5b7-c671-4fb9-b696-87b780a4ffda","resolution":{"observed_at":"2026-07-09T16:36:21.666582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.681074Z","title":"Combining Missing Data Imputation and Internal Validation in Clinical Risk Prediction Models","venue":null,"work_id":"2ea0766b-6f6d-48ff-b0ab-ea4757ee955a","year":2025},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:ac15741229aaabd7914a129959b0c57131d413f5edbabed296865b2608257313","observation_id":"0c5591bb-90ec-4e83-b319-6584067c8e65","resolution":{"observed_at":"2026-07-09T16:36:21.682416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.675139Z","title":"Multiple imputation of discrete and continuous data by fully conditional specification","venue":null,"work_id":"f3916761-af3f-4a29-8577-8ae1a0c27ee4","year":2007},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:ba4f94d59de6d92a16d2c9a6286551c895087fe3ced1874a19cd1df24b00ad78","observation_id":"d548ea16-8451-492d-84c4-9625dc5c6af7","resolution":{"observed_at":"2026-07-09T16:36:21.676485Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.647302Z","title":"Multiple imputation of missing data under missing at random: compatible imputation models are not sufficient to avoid bias if they are mis-specified","venue":null,"work_id":"e9bf16e0-9da9-4ba6-a12f-95f8337599c3","year":2023},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:ba8d367be3fb0461dcbb1f7f87cfd3db33be001186ff144d7f031772fa5896fb","observation_id":"e4512590-3ef0-4adc-b7ba-a6e37fa2c2ef","resolution":{"observed_at":"2026-07-09T16:36:21.648697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.656907Z","title":"Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study","venue":null,"work_id":"cc5a079c-c9c6-402c-abe5-0958e04b8cd0","year":null},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:8345ffac4ea38c7274a857aac242e20f8513fa46f59afb6791bcde1197ad729b","observation_id":"70f69c49-40e1-468b-b03b-dabe177015e9","resolution":{"observed_at":"2026-07-09T16:36:21.658536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.653281Z","title":"Comparison of imputation methods for missing laboratory data in medicine","venue":null,"work_id":"8928ce33-153b-4255-8db0-8b3b67ca1d52","year":2013},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:bb614ea6ac8d6759ddd19c67f8536d6348129d5964b6fc56c9fb300f1613e356","observation_id":"d6c45716-5df2-4b2a-ba08-5482e3589c14","resolution":{"observed_at":"2026-07-09T16:36:21.654542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.690742Z","title":"MissForest—non-parametric missing value imputation for mixed-type data","venue":null,"work_id":"958af9d6-78d3-4cb1-8803-d90297cf7959","year":2012},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:4f4afc151c4b966e676c7c4e3de4142c31cac9854245cc81db864609036e8cb7","observation_id":"cfe724cb-bdcf-44d4-b8eb-857a8361d367","resolution":{"observed_at":"2026-07-09T16:36:21.692021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.667139Z","title":"Missing value estimation methods for DNA microarrays","venue":null,"work_id":"77cb9269-9470-45b3-9091-70b7cbe929eb","year":2001},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:9a71646344b49ab03d0400ae3c66364d9076e07c0bba973362322b0385d6dd76","observation_id":"f523722c-83d0-4af7-9297-500f3963f2ac","resolution":{"observed_at":"2026-07-09T16:36:21.668690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.673204Z","title":"Imputation and missing indicators for handling missing data in the development and deployment of clinical prediction models: A simulation study","venue":null,"work_id":"5d42433c-e970-4233-8018-5ca20a072da6","year":2023},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:5ba0ba1fd051aa684b10b21f281faa5a5d0dd5e9bd2740ec2850cb3cedbed5e0","observation_id":"298f98e4-19c5-447a-aa62-ac403c73fec8","resolution":{"observed_at":"2026-07-09T16:36:21.674586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.671188Z","title":"Minimum sample size for developing a multivariable prediction model: PART II - binary and time-to-event outcomes","venue":null,"work_id":"5af8c950-a04c-4f3d-8412-92a2fc0cbed7","year":2019},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:65b0194e17e176e9ca8a6391b7f7cbf0eac9e2bdaccca9979f1b25047e5a1ba0","observation_id":"5c1cf168-4531-48ff-961d-7fdb1561ec5a","resolution":{"observed_at":"2026-07-09T16:36:21.672582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.649252Z","title":"Generating missing values for simulation purposes: a multivariate amputation procedure","venue":null,"work_id":"88b34dbc-ea19-40db-8d84-1dc4cd86bb3f","year":2018},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:076787eb6b54e650c3376ba20fd99d12d54848ab382485c2f811802ce517b78c","observation_id":"d783f06c-86a3-45ba-a6f5-0256d375bd02","resolution":{"observed_at":"2026-07-09T16:36:21.650655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.621890Z","title":"Evaluation of Four Multiple Imputation Methods for Handling Missing Binary Outcome Data in the Presence of an Interaction between a Dummy and a Continuous Variable","venue":null,"work_id":"04730cd6-4849-4cac-a6d2-26f80aa315d0","year":2021},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:e1b2b2fbb67e795dae7439b22a52a33356cae3e0d54f81dd0a1baf7d41df7374","observation_id":"2a20a5fa-7268-4ccb-a4f8-2247f9e44f02","resolution":{"observed_at":"2026-07-09T16:36:21.623267Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.639911Z","title":"missForestPredict—Missing data imputation for prediction settings","venue":null,"work_id":"7e9915af-d7fb-44a7-9e8c-a15da6d41f64","year":2025},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:e64455429a8efe0ae74bc651022759985a043879be9a73b2bb76afa111b21801","observation_id":"f4988029-588c-4db9-9dfa-ace1539d1cb2","resolution":{"observed_at":"2026-07-09T16:36:21.641166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.684822Z","title":"Methods for significance testing of categorical covariates in logistic regression models after multiple imputation: power and applicability analysis","venue":null,"work_id":"fb0d5094-36fd-4880-88fe-923b84914cdb","year":2017},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:4ef67b1652df9ed3ee407912675150a9b6f329de4d4ae1064ddf995286c8e32b","observation_id":"699d17a1-b6b2-46ed-b24b-ca18d8f46dd9","resolution":{"observed_at":"2026-07-09T16:36:21.686147Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.638013Z","title":"psfmi: Prediction Model Pooling, Selection and Performance Evaluation Across Multiply Imputed Datasets","venue":null,"work_id":"07c81ef1-6bb1-480f-90da-ba291a625277","year":2023},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:3855b21ccdba8c6ec592dc41e257a0ced30704cd2a33f809db94a9df39b3fd0c","observation_id":"a0c408d0-97fa-4264-95ea-8bedc437e1ec","resolution":{"observed_at":"2026-07-09T16:36:21.639365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.682954Z","title":"Re-evaluation of the comparative effectiveness of bootstrap- based optimism correction methods in the development of multivariable clinical prediction models","venue":null,"work_id":"9d32d082-38d7-48a7-a1e6-f740783d5439","year":2021},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:5bff3074a6596f8ebfec97cc521f3a1a622804f6027c65cb7f7fdd39ff0f524d","observation_id":"33bdc63d-d19c-4dc5-9265-56eefae7cda1","resolution":{"observed_at":"2026-07-09T16:36:21.684299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.677032Z","title":"Population median imputation was noninferior to complex approaches for imputing missing values in cardiovascular prediction models in clinical practice","venue":null,"work_id":"64d45da2-9716-41e9-bab8-17ca33c87a8b","year":2022},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:23461576cf2d21a078bf9e24e9a7b6ccc774139b420514769a7f8b2d54fc7d24","observation_id":"148bab80-8fe5-4253-8d09-9a9d0a179b3b","resolution":{"observed_at":"2026-07-09T16:36:21.678415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.630148Z","title":"Neural Networks and the Bias/Variance Dilemma","venue":null,"work_id":"84e8e4ff-e7ef-4e1b-a576-2f55843e3266","year":1992},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:aded2470570b812981391e5493e1bee4753126a1f0a0a4063b3969664f21956e","observation_id":"1cb7551b-5719-4d61-b5ec-11c79c922898","resolution":{"observed_at":"2026-07-09T16:36:21.631432Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.688590Z","title":"Development and Reporting of Prediction Models: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals","venue":null,"work_id":"3602dd85-d571-4e55-8891-b97197863a35","year":null},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:6c32487da2119ae81f9a955c4d58ebe82461899c0a544b5a6022f428845656b3","observation_id":"cabc02cf-96b9-499e-8006-7f1cc43c1a86","resolution":{"observed_at":"2026-07-09T16:36:21.690162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.678963Z","title":"Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis","venue":null,"work_id":"5a660aa9-63db-42c6-a48b-9e40797d24fd","year":null},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:52222496411d5b39353db5024db9cdbcb4dad0f5d816a6a3669a8d633367fd69","observation_id":"e305b7b5-6ae6-4331-834f-a18c5cdb0d67","resolution":{"observed_at":"2026-07-09T16:36:21.680540Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.655035Z","title":"Missing Data in Clinical Research: A Tutorial on Multiple Imputation","venue":null,"work_id":"d083a57c-fb00-4d6d-ac60-d46d7f46a97e","year":1916},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:25f4a529702061354ee4ffcd95442260114f5813516a58ddf842dbc43d5a216f","observation_id":"89c993f0-66b4-45f7-a541-aca9b7404da3","resolution":{"observed_at":"2026-07-09T16:36:21.656345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.669256Z","title":"Developing prediction models for clinical use using logistic regression: an overview","venue":null,"work_id":"53acea4c-ccb3-4228-944b-ca7125e78db2","year":2072},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:5d7affa51f1c974f21a5a83b102541849c5f3ce18a844d5a966295d4673daa7b","observation_id":"8ad6a109-103f-473e-8df7-3365a2f211ea","resolution":{"observed_at":"2026-07-09T16:36:21.670647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.625727Z","title":"Missing data and prediction: the pattern submodel","venue":null,"work_id":"59e90498-e113-451e-9629-80538be0e6dc","year":2020},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:fb603fe15c0f8c8e9a42709a96305871951be51c1281d2c138ed5170d47d3a13","observation_id":"31d9ae95-fcf5-4fd7-86ef-a953aed72486","resolution":{"observed_at":"2026-07-09T16:36:21.627328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.645403Z","title":null,"venue":null,"work_id":"462b99ea-c8f4-4fac-abde-0c0c55fe9144","year":null},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:5e7871c0fc7042f2b63a28108205be53ab69b9602ffd63052caa5b44dad8eab4","observation_id":"bfea6a0f-0b28-46a7-bbb4-e43cbbdb89f7","resolution":{"observed_at":"2026-07-09T16:36:21.646753Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.643465Z","title":"Just Another Variable","venue":null,"work_id":"b2eaba00-c9b8-4681-a682-d35dedeaea86","year":null},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:624a83dec1dbbc113a9eaafee9f9dbf09c3333af9037a7d668ad02d0a74709c1","observation_id":"e48f33d8-247f-408f-b7d1-19eaf632cb25","resolution":{"observed_at":"2026-07-09T16:36:21.644834Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.651213Z","title":"Predictive Mean Matching (pmm) was applied to both continuous and categorical variables, identifying the 10 closest donors for imputation","venue":null,"work_id":"eb887562-2c2a-4838-bca0-a8c8b8433643","year":null},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:62b60711c67ee0150cc8b4116d51a8420fdacc0004646bbcef6d8217b8c7a7b9","observation_id":"352bc9c9-32e1-43a8-b5b8-2534fb9f636e","resolution":{"observed_at":"2026-07-09T16:36:21.652775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.628008Z","title":"To rigorously prevent data leakage during model training, the primary outcome was deliberately excluded from the imputation predictor pool","venue":null,"work_id":"7f376fa2-100c-4dd3-a236-e4e0040c1edc","year":null},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:7f217488048a133e6651fec3f5ec2eb9648a1c6a3e12b27ae383ef94cd0b1ba7","observation_id":"e5a8ac48-29cd-4d49-af98-b2f22c395ce9","resolution":{"observed_at":"2026-07-09T16:36:21.629624Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-07-09T16:36:21.633862Z","title":"Missing continuous variables were imputed using the median of the neighbors, while missing categorical variables were imputed using the maximum category (mode)","venue":null,"work_id":"9ddf0dca-7ef3-4915-b4c9-f7414d669dbf","year":1927},"citing_paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-09T16:26:45.951896Z"},"links":{"citing_paper":"/paper/2607.07247"},"observation_digest":"sha256:5a21234ba5601fa35185486ec68ceb86bb7290eeb3b0bf775274597c8cb1b062","observation_id":"1c6a921d-59bb-431f-b310-702bc745e3ac","resolution":{"observed_at":"2026-07-09T16:36:21.635252Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2607.07247","last_updated":"2026-07-08T10:27:45Z","latest_version":1,"primary_category":"stat.ME","snapshot_observed_at":"2026-08-04T11:55:05.192862Z","submitted_at":"2026-07-08T10:27:45Z","title":"Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data"},"reference_resolution":{"displayed":36,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":34},"total_outbound_references":36},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2607.07247."}