{"id":"W4286377217","doi":"","title":"Physician Experience Design (PXD): More Usable Machine Learning Prediction for Clinical Decision Making.","year":2022,"lang":"en","type":"article","venue":"PubMed","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Services and Policy Research; Public Health Ontario; University of Toronto","funders":"","keywords":"Artificial intelligence; Computer science; Machine learning; USable; Sample (material); Delirium; Identification (biology); Process (computing); Medicine; Intensive care medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01967137,0.001082235,0.0003884068,0.001183948,0.0005933066,0.003217513,0.001573403,0.0009720576,0.005418102],"category_scores_gemma":[0.0751598,0.0006353069,0.0009473162,0.0006286486,0.0009953111,0.00316902,0.003529957,0.001462324,0.0009127451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001587449,"about_ca_system_score_gemma":0.002138379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001516068,"about_ca_topic_score_gemma":0.00290848,"domain_scores_codex":[0.9852782,0.01079483,0.001044256,0.001124282,0.001529371,0.0002288931],"domain_scores_gemma":[0.9327294,0.05155664,0.003413755,0.006456397,0.004554377,0.001289432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001972864,0.001599562,0.06401695,0.006143913,0.0004412622,0.000835192,0.02394962,0.03582134,0.01863621,0.0504738,0.02844187,0.7676674],"study_design_scores_gemma":[0.001566621,0.005950556,0.03793289,0.003259389,0.0006211529,0.001495093,0.009000478,0.4969762,0.03412341,0.1234085,0.2851778,0.0004879136],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1120134,0.0007136905,0.8569283,0.005486608,0.0001969316,0.00268868,0.00189394,0.008343716,0.01173474],"genre_scores_gemma":[0.3034998,0.0002684339,0.6904067,0.0007501318,0.00004659609,0.001409253,0.001525812,0.0003310966,0.001762162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01967137,"threshold_uncertainty_score":0.1040335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09227980623753226,"score_gpt":0.3652475705669225,"score_spread":0.2729677643293903,"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."}}