{"id":"W4304205030","doi":"10.1371/journal.pdig.0000124","title":"High resolution data modifies intensive care unit dialysis outcome predictions as compared with low resolution administrative data set","year":2022,"lang":"en","type":"article","venue":"PLOS Digital Health","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Diabetes and Digestive and Kidney Diseases","keywords":"Data set; Resolution (logic); Outcome (game theory); Dialysis; Intensive care unit; Set (abstract data type); Computer science; Medicine; Intensive care medicine; Artificial intelligence; Mathematics; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02590325,0.0007338008,0.0009568316,0.001580205,0.0007498779,0.004247996,0.001304899,0.001243013,0.00219229],"category_scores_gemma":[0.09336574,0.000625291,0.002027907,0.002532717,0.0007905542,0.002410296,0.001785403,0.001963706,0.0007714277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008239045,"about_ca_system_score_gemma":0.001038467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006609228,"about_ca_topic_score_gemma":0.003916875,"domain_scores_codex":[0.9656463,0.02355323,0.001899185,0.004138418,0.003945401,0.000817508],"domain_scores_gemma":[0.8805389,0.08917668,0.00893632,0.01649021,0.003500621,0.001357333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00341515,0.001552188,0.8700221,0.0002552765,0.002247472,0.0005482016,0.0008454956,0.04296036,0.002763135,0.00422532,0.00297233,0.06819306],"study_design_scores_gemma":[0.0004303548,0.00162124,0.7406827,0.0002956222,0.001233406,0.0007248518,0.001749042,0.2256915,0.006540672,0.01100188,0.009777407,0.0002512696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9621253,0.0005973318,0.02697167,0.001892677,0.0001517024,0.0001889525,0.004100737,0.0003834305,0.003588222],"genre_scores_gemma":[0.9843351,0.0001528087,0.01107953,0.0002734261,0.00006138007,0.00006781183,0.003501129,0.00003746586,0.0004912711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02590325,"threshold_uncertainty_score":0.1369911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1975963683659027,"score_gpt":0.3841612451661636,"score_spread":0.1865648768002609,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}