{"id":"W3211007768","doi":"10.24908/pceea.vi0.10755","title":"EMPLOYING MULTIFACETED TEACHING AND LEARNING COMPONENTS TO FOSTER CEAB GRADUATE ATTRIBUTE DEVELOPMENT","year":2018,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Engineering Education and Curriculum Development","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Accreditation; Medical education; Quality (philosophy); Graduate students; Collaborative learning; Peer learning; Engineering education; Teamwork; Computer science; Engineering management; Psychology; Mathematics education; Engineering; Medicine; Management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006530616,0.0002092816,0.000182902,0.0003623571,0.0004018918,0.0001320296,0.000218025,0.0001083602,0.00001274645],"category_scores_gemma":[0.0007667505,0.0002231318,0.00003784619,0.0003917423,0.00001167181,0.0001739732,0.0000455147,0.0004628388,0.00003372699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001872916,"about_ca_system_score_gemma":0.0001845314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006728083,"about_ca_topic_score_gemma":0.0006604096,"domain_scores_codex":[0.9987535,0.00000977128,0.0003447514,0.0002085769,0.0002833963,0.0003999351],"domain_scores_gemma":[0.9990776,0.00003939203,0.0001141322,0.00007956444,0.0003679735,0.0003212951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001164706,0.0003013354,0.4236632,0.00238654,0.001282125,5.475733e-7,0.1609216,0.03357849,0.1086778,0.003178288,0.220862,0.04513643],"study_design_scores_gemma":[0.0003432402,0.00002688604,0.7430907,0.0006305952,0.00003942023,0.000008244535,0.001519749,0.01400691,0.01404875,0.00002091246,0.2254273,0.0008371937],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943777,0.00004341038,0.0002477294,0.001565495,0.00179773,0.0003229729,0.000004387266,0.0002537192,0.001386867],"genre_scores_gemma":[0.9890519,0.000003017997,0.009186286,0.000240304,0.0001538064,0.00006953537,0.00001158979,0.00005426887,0.001229295],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3194276,"threshold_uncertainty_score":0.9099052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01499357040390982,"score_gpt":0.2169041193240272,"score_spread":0.2019105489201174,"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."}}