{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02270458,0.001402562,0.001666271,0.002452006,0.0008726627,0.001762208,0.00124671,0.001015816,0.001268894],"category_scores_gemma":[0.04590772,0.0003011487,0.002546327,0.001366812,0.0008042863,0.001352451,0.00117957,0.002021949,0.0003193053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009592267,"about_ca_system_score_gemma":0.000970134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004931448,"about_ca_topic_score_gemma":0.003158408,"domain_scores_codex":[0.9932394,0.003483185,0.0005813462,0.001155179,0.001091498,0.0004494528],"domain_scores_gemma":[0.9518631,0.04024778,0.002383311,0.002364966,0.002718084,0.0004227507],"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":[0.002589769,0.001072776,0.576536,0.0002871367,0.001169012,0.0006232968,0.001395632,0.1465987,0.004235192,0.002101063,0.005040701,0.2583508],"study_design_scores_gemma":[0.00005557862,0.0003172516,0.07096569,0.00005524296,0.000159181,0.0001474969,0.0002581098,0.9234162,0.001472851,0.002598147,0.0005099206,0.00004437719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8444992,0.0005459627,0.151665,0.0006241178,0.0001222019,0.0003904497,0.0007648182,0.0004976036,0.0008906194],"genre_scores_gemma":[0.9811831,0.0000720591,0.01733368,0.00005611872,0.00004376002,0.0001999339,0.000811031,0.00003097852,0.0002693436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02270458,"threshold_uncertainty_score":0.1200747,"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."}}