{"id":"W2121705641","doi":"10.24908/pceea.v0i0.5858","title":"TEACHING ASSISTANT TRAINING TO ENHANCE GRADUATE ENGINEERING EDUCATION","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Graduate students; Training (meteorology); Medical education; Graduate education; Computer science; Science and engineering; Engineering management; Engineering education; Mathematics education; Psychology; Engineering ethics; Engineering; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0008183583,0.000334218,0.0002927174,0.0005929645,0.0001423524,0.0001752177,0.0004920279,0.0001843337,0.000008320226],"category_scores_gemma":[0.001760886,0.0003804466,0.0001067763,0.000736366,0.000009867071,0.0004260961,0.00004504679,0.0006621602,0.00002995882],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005688205,"about_ca_system_score_gemma":0.0008414153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003107828,"about_ca_topic_score_gemma":0.0006930414,"domain_scores_codex":[0.998035,0.000009086931,0.0004769415,0.0002945015,0.0005738742,0.0006105975],"domain_scores_gemma":[0.9984659,0.00005447962,0.0001728015,0.0001941543,0.0004495168,0.0006631743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009450327,0.0001932963,0.01036334,0.00124032,0.0004371696,6.554648e-7,0.03803528,0.6303061,0.1768155,0.02561317,0.1012471,0.01573861],"study_design_scores_gemma":[0.0006517997,0.0001480508,0.04714799,0.002992315,0.0002240391,0.00005474683,0.009258856,0.1681314,0.1002564,0.000332791,0.6673484,0.003453245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9639382,0.0005152214,0.0009508186,0.002867218,0.009658439,0.00095668,0.00002654505,0.001116314,0.01997052],"genre_scores_gemma":[0.985446,0.000004294827,0.01190567,0.0001694996,0.0004979496,0.0001786397,0.00001129855,0.0001371442,0.001649502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5661014,"threshold_uncertainty_score":0.9998648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01405197741083868,"score_gpt":0.2453895456896839,"score_spread":0.2313375682788452,"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."}}