{"id":"W4321636216","doi":"10.2196/44325","title":"Predicting Generalized Anxiety Disorder From Impromptu Speech Transcripts Using Context-Aware Transformer-Based Neural Networks: Model Evaluation Study","year":2023,"lang":"en","type":"article","venue":"JMIR Mental Health","topic":"Mental Health via Writing","field":"Psychology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Impromptu; Psychology; Anxiety; Logistic regression; Receiver operating characteristic; Artificial intelligence; Transformer; Artificial neural network; Computer science; Natural language processing; Cognitive psychology; Machine learning; Psychiatry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002143076,0.0004754019,0.0006459456,0.0002161893,0.001006252,0.00005655176,0.0002851704,0.0002077111,0.0004250765],"category_scores_gemma":[0.00000638874,0.0004998244,0.0001870475,0.0007046788,0.0000668862,0.0002656128,0.00003156024,0.0005900775,0.00003409904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009317916,"about_ca_system_score_gemma":0.0003114174,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01303059,"about_ca_topic_score_gemma":0.004808548,"domain_scores_codex":[0.9940509,0.001221836,0.001307123,0.001047965,0.0009957078,0.001376527],"domain_scores_gemma":[0.9985034,0.00009887653,0.00037106,0.0004983905,0.00008222288,0.0004460769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002786758,0.003918656,0.3767065,0.0005688228,0.0002631651,0.0000314802,0.07526154,0.06517654,0.001460763,0.00004091416,0.001847579,0.4719373],"study_design_scores_gemma":[0.009756178,0.0007058911,0.04260708,0.000146197,0.00005134013,0.000009051263,0.02375443,0.9225187,0.00003239243,0.00003305399,0.0000387353,0.0003469264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844695,0.0007128742,0.002310742,0.001059005,0.001795267,0.00856599,0.0005096493,0.0004941219,0.00008289055],"genre_scores_gemma":[0.9945836,0.00002123191,0.0003855049,0.002062433,0.0003333452,0.001031384,0.001382515,0.0001339262,0.0000660257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8573422,"threshold_uncertainty_score":0.9997453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1029138452098545,"score_gpt":0.4320341449449156,"score_spread":0.3291202997350611,"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."}}