{"id":"W4413679691","doi":"10.1109/compsac65507.2025.00109","title":"Personalized Mental Health Assistance with Large Language Models","year":2025,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Mental health; Human–computer interaction; Psychology; Psychiatry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001736563,0.00108823,0.0005988537,0.0005232505,0.0003924987,0.0009657619,0.001013054,0.001261754,0.004008172],"category_scores_gemma":[0.008052106,0.0003327483,0.0008966714,0.0003772758,0.0003539371,0.001392711,0.001600613,0.00144961,0.002915297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006149295,"about_ca_system_score_gemma":0.00102154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003490715,"about_ca_topic_score_gemma":0.006622416,"domain_scores_codex":[0.9987234,0.0008147336,0.00005534938,0.0002435607,0.00009841795,0.00006442169],"domain_scores_gemma":[0.9962991,0.002918302,0.0001104581,0.0003892203,0.0002008844,0.00008207502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001557169,0.001211717,0.01446638,0.0009516971,0.0002800467,0.0009082612,0.001378044,0.3180685,0.02033515,0.006379349,0.04847061,0.5859931],"study_design_scores_gemma":[0.00009835404,0.0001757742,0.001120617,0.00004418198,0.00006293578,0.0001607022,0.0002348111,0.9743895,0.004611919,0.01110328,0.007958402,0.00003947415],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1732741,0.002397787,0.7696021,0.005375138,0.0004953577,0.0006891996,0.007003592,0.03310607,0.008056665],"genre_scores_gemma":[0.7981585,0.0004367739,0.1873862,0.001507517,0.0001588602,0.0005341197,0.006634814,0.000431771,0.00475127],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004008172,"threshold_uncertainty_score":0.01340866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01145985500713928,"score_gpt":0.3151821270652329,"score_spread":0.3037222720580936,"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."}}