{"id":"W4382630776","doi":"10.3233/shti230430","title":"A Machine Learning Study to Predict Anxiety on Campuses in Lebanon","year":2023,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Mitacs","keywords":"Anxiety; Mental health; Machine learning; Perceptron; Artificial intelligence; Support vector machine; Logistic regression; Random forest; Multilayer perceptron; Multidisciplinary approach; Computer science; Artificial neural network; Psychology; Applied psychology; Psychiatry; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.001360457,0.0001661297,0.0004202939,0.001441421,0.0002504285,0.000004438106,0.0001431267,0.0001184203,0.00000879915],"category_scores_gemma":[0.0003500036,0.0001466134,0.00001486178,0.001811537,0.0001359493,0.00005778679,0.0002908506,0.0006900832,0.00009248679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003204687,"about_ca_system_score_gemma":0.00008470373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005081454,"about_ca_topic_score_gemma":0.001928758,"domain_scores_codex":[0.9981982,0.0001105559,0.0007876737,0.0001950964,0.0001256572,0.00058288],"domain_scores_gemma":[0.9992605,0.0002521494,0.0001451307,0.0002500463,0.00002163048,0.00007050161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001199464,0.0002540954,0.819231,0.0005728976,0.00002896796,0.00001569904,0.1117693,0.0001014515,1.466452e-7,0.002472934,0.001198187,0.06423537],"study_design_scores_gemma":[0.00356235,0.008656008,0.3790418,0.000572138,0.000007522055,0.00002303702,0.5316893,0.00116235,0.000003650108,0.001183162,0.07376777,0.0003309101],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915069,0.001539866,0.0000105488,0.003719825,0.0005571483,0.001302603,0.00001098737,0.0003204341,0.001031731],"genre_scores_gemma":[0.9927983,0.004255049,0.0001002133,0.002279904,0.00001665331,0.0002549377,0.000006032793,0.00001118705,0.0002777734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4401892,"threshold_uncertainty_score":0.5978719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08323486827209696,"score_gpt":0.4562068593630944,"score_spread":0.3729719910909974,"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."}}