{"id":"W1966083667","doi":"10.1503/cmaj.061555","title":"I see faces","year":2007,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Healthcare Systems and Challenges","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Face (sociological concept); Medical school; Medical education; Medicine; Computer science; Linguistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003652418,0.001097448,0.0004353823,0.00067581,0.003248936,0.002382448,0.0006501166,0.002567262,0.2240864],"category_scores_gemma":[0.002992147,0.0003109563,0.0005499649,0.0002854512,0.001531901,0.003422201,0.00228189,0.002831412,0.1224358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006768093,"about_ca_system_score_gemma":0.0004678404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006790392,"about_ca_topic_score_gemma":0.009368653,"domain_scores_codex":[0.9995494,0.00007505715,0.000009603229,0.00006096734,0.0001797192,0.0001251983],"domain_scores_gemma":[0.9992903,0.00007984423,0.00005195197,0.00004618531,0.0002251531,0.0003065659],"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":[0.00007253012,0.00006840672,0.001904556,0.000105085,0.00001542433,0.001506194,0.004134428,0.00004532322,0.003550731,0.004899602,0.9040616,0.07963607],"study_design_scores_gemma":[0.00001306898,0.00006776099,0.002386708,0.0001838676,0.000009009331,0.007107809,0.006346387,0.00004538866,0.0007049265,0.00216121,0.9809377,0.00003626794],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02445472,0.01193621,0.00662602,0.09903365,0.01665915,0.0001490014,0.001283187,0.00306096,0.8367972],"genre_scores_gemma":[0.1175345,0.009004035,0.004979507,0.07033369,0.004010105,0.00008835971,0.0004396118,0.0005821873,0.7930281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2240864,"threshold_uncertainty_score":0.7496437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04754223804502285,"score_gpt":0.4117509763703249,"score_spread":0.3642087383253021,"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."}}