{"id":"W4293393965","doi":"10.1016/j.health.2022.100100","title":"A machine learning model for predicting, diagnosing, and mitigating health disparities in hospital readmission","year":2022,"lang":"en","type":"article","venue":"Healthcare Analytics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Pipeline (software); Computer science; Machine learning; Process (computing); Artificial intelligence; Data collection; Data mining; Statistics","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":[0.005400137,0.0006651519,0.000816872,0.0009471655,0.0007152208,0.001229351,0.00131847,0.001230892,0.001458663],"category_scores_gemma":[0.0132872,0.0002807747,0.0006915857,0.0007034654,0.0005163892,0.001395803,0.0008873343,0.001742975,0.0002763296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001415273,"about_ca_system_score_gemma":0.002248752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01188461,"about_ca_topic_score_gemma":0.009085951,"domain_scores_codex":[0.9988367,0.0004879237,0.00007594408,0.0002774744,0.000218012,0.000103954],"domain_scores_gemma":[0.9943299,0.004189042,0.0004863354,0.0002615865,0.0005920336,0.0001409771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004375485,0.000459696,0.02818251,0.00007845164,0.0001277795,0.0001297276,0.0001412883,0.8646851,0.000881876,0.007544519,0.003970153,0.0933614],"study_design_scores_gemma":[0.00001008646,0.00002972431,0.0008319636,0.000006987526,0.000008531368,0.000009639843,0.00000711608,0.9951573,0.0001801349,0.00358187,0.0001718576,0.000004794489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2543187,0.001054774,0.7324232,0.006084104,0.0002546541,0.0003522534,0.001417729,0.001041611,0.003052927],"genre_scores_gemma":[0.8951312,0.0003043342,0.09976858,0.000608043,0.0002145858,0.000303099,0.0009250763,0.00003611514,0.002709029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01188461,"threshold_uncertainty_score":0.02855897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02898411658770357,"score_gpt":0.316319202835405,"score_spread":0.2873350862477014,"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."}}