{"id":"W4206158942","doi":"10.2196/33063","title":"Panic Attack Prediction Using Wearable Devices and Machine Learning: Development and Cohort Study","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes","field":"Psychology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Taiwan University; Ministry of Science and Technology, Taiwan","keywords":"Anxiety; Beck Anxiety Inventory; Beck Depression Inventory; Panic disorder; Panic; Machine learning; Artificial intelligence; Psychology; Clinical psychology; Psychiatry; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009868217,0.0002126015,0.0002831537,0.000279268,0.0006383842,0.00006310951,0.0001704672,0.0001079412,0.001348936],"category_scores_gemma":[0.0001351438,0.0001850469,0.00002252165,0.0005382486,0.0001046915,0.0002451116,0.0003809532,0.0006063866,0.00003359339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001007174,"about_ca_system_score_gemma":0.0001029344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004174489,"about_ca_topic_score_gemma":0.00001221517,"domain_scores_codex":[0.9977318,0.0001794216,0.0006133165,0.0002482085,0.0009087066,0.0003185578],"domain_scores_gemma":[0.9990353,0.0001830618,0.0002790721,0.0001649433,0.00008212753,0.0002554682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005261831,0.0005676835,0.8726401,0.00007558446,0.0002166329,0.00001004737,0.01996022,0.00001095353,4.261896e-7,0.000008468894,0.000632983,0.1058242],"study_design_scores_gemma":[0.00365032,0.0008901472,0.7134265,0.00008485884,0.0001606236,0.0003327916,0.05874173,0.01185825,0.000008420503,0.00002752891,0.210412,0.0004067295],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926383,0.002022736,0.001047301,0.00003939982,0.0004444204,0.0008598599,0.00001389121,0.0001185846,0.002815513],"genre_scores_gemma":[0.9969172,0.0009706022,0.0007230128,0.0002514047,0.00007477756,0.0003835923,0.00005035081,0.00002374112,0.0006053254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2097791,"threshold_uncertainty_score":0.999564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05771361525312357,"score_gpt":0.3584942906922109,"score_spread":0.3007806754390874,"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."}}