{"id":"W4399126047","doi":"10.14740/jocmr5167","title":"Predicting Dropout From Cognitive Behavioral Therapy for Panic Disorder Using Machine Learning Algorithms","year":2024,"lang":"en","type":"article","venue":"Journal of Clinical Medicine Research","topic":"Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nagoya City University; Ministry of Health, Labour and Welfare","keywords":"Dropout (neural networks); Panic disorder; Medicine; Cognitive behavioral therapy; Cognition; Artificial intelligence; Machine learning; Algorithm; Clinical psychology; Psychotherapist; Psychiatry; Computer science; Psychology; Anxiety","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005950231,0.0005170563,0.0007927775,0.001527905,0.0002868885,0.0008609294,0.0005127637,0.0005736765,0.0008160469],"category_scores_gemma":[0.01464064,0.0001806236,0.0008564036,0.0005481429,0.0002375616,0.0004967912,0.000430458,0.001100125,0.0001793165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007132476,"about_ca_system_score_gemma":0.0008750049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002530678,"about_ca_topic_score_gemma":0.002259393,"domain_scores_codex":[0.9987862,0.0007447849,0.00009092245,0.0001301932,0.0001345697,0.0001133373],"domain_scores_gemma":[0.9890392,0.009088037,0.0008093233,0.0002517428,0.0005575117,0.0002541474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001112774,0.001456788,0.6809469,0.0001816857,0.0005343602,0.00008997812,0.0002465905,0.1125023,0.0004948709,0.0004288125,0.002446867,0.1995581],"study_design_scores_gemma":[0.00008847187,0.000831284,0.1230701,0.0001329278,0.0001609117,0.00008597965,0.0001308526,0.8719675,0.0006209809,0.002414376,0.000471507,0.00002514395],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9437451,0.001074257,0.05232618,0.0009255483,0.00005266787,0.0002636671,0.0004549573,0.0002500476,0.0009075578],"genre_scores_gemma":[0.9856464,0.0001556275,0.01343216,0.00007844577,0.00003031492,0.0001275565,0.0003672332,0.000008476806,0.0001537956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005950231,"threshold_uncertainty_score":0.03146821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4509055922669832,"score_gpt":0.6315667785920427,"score_spread":0.1806611863250595,"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."}}