{"id":"W4307338507","doi":"10.1001/jamapsychiatry.2022.3391","title":"Being Precise About Precision Mental Health","year":2022,"lang":"en","type":"article","venue":"JAMA Psychiatry","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto; SickKids Foundation; Centre for Addiction and Mental Health","funders":"","keywords":"Precision medicine; Mental health; MEDLINE; Psychology; Medicine; Computer science; Psychiatry; Political science; Pathology","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":[0.08889285,0.001432488,0.002924089,0.004667202,0.004517609,0.01167942,0.003287119,0.01301732,0.006143359],"category_scores_gemma":[0.2068677,0.0009618496,0.002093554,0.002207601,0.05506314,0.02733846,0.008297855,0.02890605,0.001899131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005271466,"about_ca_system_score_gemma":0.008087806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006027843,"about_ca_topic_score_gemma":0.003644655,"domain_scores_codex":[0.9419109,0.02589978,0.005017745,0.006648776,0.0184583,0.002064438],"domain_scores_gemma":[0.8050626,0.1477032,0.009886736,0.01877814,0.01639775,0.002171533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000225479,0.00004312635,0.002474331,0.0007298604,0.000222549,0.0001446375,0.002645719,0.0009825383,0.0003273609,0.9135712,0.0334823,0.04515094],"study_design_scores_gemma":[0.00007239359,0.0001204478,0.001127809,0.001141713,0.0001039419,0.0003068357,0.0007213137,0.000468048,0.0005726534,0.9264106,0.06886074,0.00009349647],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.004977397,0.05431661,0.05934316,0.8294758,0.009885269,0.00007817971,0.0004542471,0.0001777807,0.04129156],"genre_scores_gemma":[0.4579358,0.0350271,0.04298399,0.4239145,0.03286675,0.0003967159,0.0003130756,0.0002515785,0.006310608],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.08889285,"threshold_uncertainty_score":0.4701159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009364088829162126,"score_gpt":0.2930790266976775,"score_spread":0.2837149378685154,"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."}}