{"id":"W4387163701","doi":"10.1109/inc457730.2023.10263141","title":"Machine Learning based approaches for Identification and Prediction of diverse Mental Health Conditions","year":2023,"lang":"en","type":"article","venue":"","topic":"Mental Health via Writing","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"","keywords":"Machine learning; Mental health; Oversampling; Artificial intelligence; Identification (biology); Computer science; Anxiety; Depression (economics); Statistical classification; Domain (mathematical analysis); Psychology; Data science; Psychiatry; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005622874,0.00005128116,0.00009057344,0.0001168749,0.0002584639,0.000006329401,0.00003035883,0.00003241372,0.0002101716],"category_scores_gemma":[0.00001988234,0.0000539174,0.00002231702,0.0001348062,0.00003766656,0.00005148355,0.00001500941,0.00005808468,0.00002628116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000038129,"about_ca_system_score_gemma":0.0000158891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002085113,"about_ca_topic_score_gemma":0.00002813404,"domain_scores_codex":[0.9992554,0.00008938047,0.0002543723,0.0001710378,0.00007891301,0.0001509479],"domain_scores_gemma":[0.9996195,0.0001016516,0.0001298292,0.00007878626,0.00001470929,0.00005555152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008524251,0.001558192,0.5497347,0.004639465,0.0003116823,0.000003115362,0.03288664,0.001515617,0.009041556,0.149135,0.09158379,0.1587379],"study_design_scores_gemma":[0.004445055,0.0008441847,0.5356426,0.0001010206,0.0000303355,0.00001008706,0.03251056,0.4198934,0.0008465119,0.0007120245,0.004786686,0.000177556],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.950928,0.0003219214,0.02728993,0.007248939,0.001155516,0.003541702,0.00288037,0.0006667972,0.005966789],"genre_scores_gemma":[0.9955004,0.00001057008,0.0003881409,0.0001068781,0.00002725659,0.0001313378,0.001990256,0.00001027694,0.001834882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4183778,"threshold_uncertainty_score":0.2301232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1475389625497981,"score_gpt":0.3952825805712057,"score_spread":0.2477436180214076,"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."}}