{"id":"W7132909979","doi":"","title":"Using a Data-Driven Population Segmentation Approach to Improve our Understanding of Mental Health and Associated Mental Healthcare Service Use Patterns in Ontario, Canada.","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Mental Health Treatment and Access","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mental health; Population; Mental health service; Health care; Service (business); Psychological intervention","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002632016,0.0003827755,0.0005743355,0.003782151,0.00255865,0.002137385,0.001472138,0.0005500402,0.001828979],"category_scores_gemma":[0.0106922,0.0004545852,0.001260484,0.008259996,0.0007499795,0.0006981232,0.002026512,0.0009041784,0.0003544958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04043465,"about_ca_system_score_gemma":0.05250966,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9901633,"about_ca_topic_score_gemma":0.992111,"domain_scores_codex":[0.9982344,0.0003624531,0.0001361627,0.0003607435,0.0006018562,0.0003043939],"domain_scores_gemma":[0.9949617,0.000896796,0.0006571176,0.0005610813,0.002535213,0.0003880717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009692498,0.00008835697,0.8585204,0.0004413494,0.0004541875,0.0003354337,0.006204139,0.01774572,0.0008282013,0.0148636,0.03518557,0.0652362],"study_design_scores_gemma":[0.00004628253,0.00003609055,0.8423313,0.0003242549,0.0001562898,0.00009023106,0.008851741,0.07219192,0.0006159536,0.00864439,0.06660605,0.0001054404],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6819168,0.003465084,0.1102,0.01493766,0.0003278389,0.002823302,0.162795,0.001013315,0.02252099],"genre_scores_gemma":[0.8520825,0.001253863,0.07429145,0.00102843,0.00006298171,0.001124602,0.06248935,0.000132902,0.00753387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04043465,"threshold_uncertainty_score":0.2933753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1997490852606519,"score_gpt":0.4460398457851664,"score_spread":0.2462907605245144,"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."}}