{"id":"W1966142025","doi":"10.1002/jclp.20155","title":"Can a matrix make a training model?: “No.” let's not throw out the Boulder model","year":2005,"lang":"en","type":"letter","venue":"Journal of Clinical Psychology","topic":"Mental Health and Psychiatry","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Psychology; Matrix model; Training (meteorology); Graduate students; TRACE (psycholinguistics); Medical education; Field (mathematics); Mental health; Matrix (chemical analysis); Applied psychology; Mental model; Psychotherapist; Cognitive science; Pedagogy; Medicine; Mathematics; Philosophy","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":[0.00588164,0.0006388674,0.0006856759,0.0005409031,0.007434257,0.004897807,0.002500607,0.02893155,0.01234887],"category_scores_gemma":[0.03662989,0.0005826586,0.0006641912,0.0004662114,0.008166914,0.01279008,0.003069944,0.0528133,0.008632903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004700946,"about_ca_system_score_gemma":0.005782999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009938323,"about_ca_topic_score_gemma":0.01943908,"domain_scores_codex":[0.9961201,0.001732901,0.0002933701,0.0004254383,0.001023436,0.0004047033],"domain_scores_gemma":[0.9895318,0.003919233,0.0007435089,0.0005618195,0.002706713,0.002536986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001921636,0.00002228692,0.0002998217,0.00003091811,0.000005130888,0.0005283201,0.0003289451,0.00004110725,0.00004917305,0.006473342,0.9845333,0.007668404],"study_design_scores_gemma":[0.00006707459,0.00007591208,0.0007468377,0.0005026786,0.000013061,0.003821773,0.005146506,0.000622805,0.0001510334,0.02838859,0.9603879,0.00007581499],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.000140003,0.0003976789,0.0001202542,0.9937727,0.004434567,0.00000326755,0.000005192679,0.0000138942,0.001112561],"genre_scores_gemma":[0.005592389,0.0009478563,0.0006122211,0.9798809,0.007649597,0.00002699618,0.0000111777,0.00003021463,0.005248629],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02893155,"threshold_uncertainty_score":0.04131103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4499622293281867,"score_gpt":0.514935677971503,"score_spread":0.06497344864331628,"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."}}