{"id":"W2010903593","doi":"10.1503/cmaj.045200","title":"Integrating medical and engineering undergraduate training","year":2005,"lang":"en","type":"letter","venue":"Canadian Medical Association Journal","topic":"Health and Medical Research Impacts","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subject (documents); Medical education; Computer science; Training (meteorology); Data science; Medicine; World Wide Web","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":[0.003400689,0.0005262513,0.0004063914,0.0004311707,0.004345117,0.002916227,0.001266373,0.03529014,0.01574819],"category_scores_gemma":[0.01199039,0.00041396,0.0006698195,0.0004197329,0.002608023,0.003359825,0.005436921,0.01672825,0.004589751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003748053,"about_ca_system_score_gemma":0.007188569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00379659,"about_ca_topic_score_gemma":0.02402657,"domain_scores_codex":[0.9937342,0.001023996,0.0004075848,0.0006967413,0.002797812,0.00133966],"domain_scores_gemma":[0.9898606,0.002121262,0.0004907341,0.0004936141,0.001363729,0.005670073],"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":[0.00006778186,0.0008248359,0.006045011,0.0001648335,0.00002281362,0.007955409,0.0006419282,0.0003118594,0.001727634,0.01488602,0.8543308,0.1130211],"study_design_scores_gemma":[0.00008955735,0.000516917,0.009714917,0.0002424509,0.00001379326,0.00995009,0.001136045,0.0006275117,0.0004295683,0.00874911,0.9684919,0.00003808518],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.006775075,0.001925707,0.001131168,0.9208169,0.02355952,0.00007488715,0.00001812221,0.0001085153,0.0455901],"genre_scores_gemma":[0.03973696,0.001420124,0.0008752732,0.8893957,0.02423126,0.00008456052,0.00002326583,0.00001999914,0.0442128],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03529014,"threshold_uncertainty_score":0.052683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04802709693440647,"score_gpt":0.3360116977682684,"score_spread":0.287984600833862,"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."}}