{"id":"W2989850715","doi":"10.2196/15601","title":"Interpretability and Class Imbalance in Prediction Models for Pain Volatility in Manage My Pain App Users: Analysis Using Feature Selection and Majority Voting Methods","year":2019,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Pain Management and Opioid Use","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"North York General Hospital; Toronto General Hospital; Lakehead University; York University","funders":"Canadian Institutes of Health Research; Mitacs; University of Toronto; York University","keywords":"Interpretability; Feature selection; Computer science; Voting; Feature (linguistics); Class (philosophy); Artificial intelligence; Machine learning; Selection (genetic algorithm); Data mining; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01104996,0.0001788465,0.0005359913,0.0003969699,0.00004569138,0.00004231559,0.00008274373,0.0003000687,0.00001437524],"category_scores_gemma":[0.001101873,0.0001578628,0.00008250061,0.0008072866,0.00006882635,0.0004885566,0.0000941151,0.000523668,2.413301e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001988032,"about_ca_system_score_gemma":0.00004220337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005592176,"about_ca_topic_score_gemma":0.0002012411,"domain_scores_codex":[0.9979602,0.0004857114,0.0006755888,0.0002300822,0.000350788,0.0002976887],"domain_scores_gemma":[0.9986894,0.0007213121,0.0001724116,0.0002041355,0.0000595371,0.0001532261],"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":[0.000167672,0.00007807655,0.9743657,0.002076467,0.0001135817,0.000001067609,0.003282638,0.000624209,0.00002487211,0.00008172892,0.00006634327,0.01911772],"study_design_scores_gemma":[0.001062872,0.0000859982,0.1933219,0.0002540839,0.0001149729,8.781586e-7,0.00165448,0.8029258,0.000004337868,0.0003154916,0.0001590988,0.0001000973],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6093687,0.00004626129,0.3893543,0.0001522755,0.0000320581,0.0009140596,0.000004574141,0.00003851555,0.00008924959],"genre_scores_gemma":[0.9471647,0.00002846913,0.05207733,0.0005438598,0.00003651346,0.0000540462,0.00004957925,0.000009048648,0.0000365176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8023016,"threshold_uncertainty_score":0.6437459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01569393128586867,"score_gpt":0.3280822275659243,"score_spread":0.3123882962800556,"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."}}