{"id":"W3215156034","doi":"","title":"Children’s mental health need in Ontario: measurement, variations in unmet need and the alignment between children’s mental health service expenditures and need","year":2020,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Ministère de l’Éducation, Gouvernement de l’Ontario; Ontario Ministry of Health and Long-Term Care","keywords":"Mental health; Mental health service; Service (business); Psychiatry; Psychology; Medicine; Gerontology; Business; Marketing","routes":{"ca_aff":false,"ca_fund":true,"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":[0.002601553,0.0002983209,0.0004662893,0.002765559,0.003422696,0.001947356,0.001282719,0.0004619325,0.002306415],"category_scores_gemma":[0.009917817,0.0004731703,0.0007424155,0.01242617,0.001872394,0.001295954,0.002288206,0.0007906296,0.0001955205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07064842,"about_ca_system_score_gemma":0.05280458,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9924605,"about_ca_topic_score_gemma":0.9968191,"domain_scores_codex":[0.996703,0.0003603319,0.0002675426,0.0002946536,0.001594084,0.0007804185],"domain_scores_gemma":[0.9915873,0.001095141,0.00262079,0.0004029924,0.003029854,0.001263888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003813226,0.0000171754,0.9726967,0.0001382281,0.00005877828,0.00007387171,0.01233917,0.0001996923,0.00008519132,0.001034175,0.00435039,0.008968646],"study_design_scores_gemma":[0.000003458137,0.000006681308,0.9912543,0.00005698936,0.00001318727,0.00001413326,0.005336332,0.00009243893,0.00002578151,0.00007447644,0.003114693,0.000007691701],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9671777,0.001640926,0.0005789803,0.003991405,0.0000413887,0.0001587973,0.01215727,0.00002560801,0.01422796],"genre_scores_gemma":[0.9919623,0.001296143,0.0008783148,0.0002083816,0.00001709949,0.0001829925,0.003422041,0.00001859474,0.002014183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07064842,"threshold_uncertainty_score":0.5125926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02963705006543144,"score_gpt":0.2225973434364664,"score_spread":0.192960293371035,"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."}}