{"id":"W3083800969","doi":"10.1016/j.jval.2020.06.009","title":"How Good Is Machine Learning in Predicting All-Cause 30-Day Hospital Readmission? Evidence From Administrative Data","year":2020,"lang":"en","type":"article","venue":"Value in Health","topic":"Heart Failure Treatment and Management","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université Laval","funders":"Xinjiang University","keywords":"Computer science; Medicine; Emergency 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":[0.06888274,0.001501415,0.001680762,0.002624829,0.0009048769,0.003432948,0.003042454,0.002765111,0.002419614],"category_scores_gemma":[0.1801039,0.0005172971,0.003509483,0.002861927,0.001979935,0.00422293,0.001203582,0.002897302,0.0009677532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003077733,"about_ca_system_score_gemma":0.003625876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05449824,"about_ca_topic_score_gemma":0.03578353,"domain_scores_codex":[0.9678777,0.02351898,0.001594889,0.002469968,0.003578675,0.0009597737],"domain_scores_gemma":[0.7249811,0.225777,0.01022991,0.01118162,0.02494334,0.002887138],"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":[0.003142299,0.0005162051,0.81363,0.00248291,0.007355716,0.0001465993,0.0005659348,0.02164892,0.00007488178,0.001695308,0.01116765,0.1375735],"study_design_scores_gemma":[0.000544795,0.002682482,0.802395,0.01037517,0.006877675,0.0003567659,0.001734308,0.1403123,0.0009786237,0.01470964,0.01876213,0.0002710077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7266781,0.1690215,0.02119261,0.05704269,0.001773726,0.0003836278,0.007705546,0.0003858715,0.01581633],"genre_scores_gemma":[0.9814922,0.01080458,0.002876103,0.00189347,0.0005148127,0.00004377531,0.001797498,0.00005109805,0.0005264949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06888274,"threshold_uncertainty_score":0.3642911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2222132342234124,"score_gpt":0.3845053589216418,"score_spread":0.1622921246982295,"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."}}