{"id":"W2886744585","doi":"10.24908/pceea.v0i0.10389","title":"EXPERIENCING ENGINEERING EDUCATION: LESSONS FROM THE COMPREHENSIVE/QUALIFYING EXAMINATIONS","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 Toronto","funders":"","keywords":"Candidacy; Medical education; Discipline; Engineering education; Engineering ethics; Pedagogy; Psychology; Mathematics education; Engineering management; Engineering; Medicine; Political science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002949595,0.0003007682,0.0002253266,0.0002980907,0.0003955353,0.0002222005,0.0006203646,0.000186904,0.0001077115],"category_scores_gemma":[0.0006822833,0.0002769355,0.0001077102,0.001059317,0.00003616805,0.0003163743,0.00004529998,0.0003817246,0.0000415879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002569844,"about_ca_system_score_gemma":0.0009681895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003622649,"about_ca_topic_score_gemma":0.002343973,"domain_scores_codex":[0.9983431,0.00000979203,0.0004703637,0.0002724652,0.0004366354,0.0004676193],"domain_scores_gemma":[0.9982331,0.0001534783,0.000195294,0.0002573005,0.0008938793,0.000266919],"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":[0.00000460446,0.0004043255,0.06967145,0.001276357,0.001100714,3.200596e-7,0.06325297,0.02554665,0.05946066,0.0711427,0.6892449,0.01889436],"study_design_scores_gemma":[0.0002875825,0.00001804377,0.4385801,0.0008397751,0.0001206654,0.00001159675,0.006342126,0.02276047,0.01636471,0.0001728194,0.5134677,0.001034383],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9626482,0.001274392,0.000489791,0.008289857,0.01597225,0.0009403481,0.00006988148,0.0007734322,0.009541822],"genre_scores_gemma":[0.9941577,0.0000373595,0.002978097,0.0004589689,0.001032988,0.0002399379,0.00003063888,0.00008158782,0.0009827331],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3689086,"threshold_uncertainty_score":0.9999683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185728006778625,"score_gpt":0.2320349646249134,"score_spread":0.2201776845571272,"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."}}