{"id":"W1148448807","doi":"10.24908/pceea.v0i0.5847","title":"DIVERSITY IN ENGINEERING UNDERGRADUATE EDUCATION: A CASE FOR NONCOGNITIVE VARIABLES IN ENGINEERING ADMISSIONS","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Diversity (politics); Variety (cybernetics); Psychology; Institution; Gauge (firearms); Engineering education; Cultural diversity; Race (biology); Medical education; Higher education; Population; Mathematics education; Computer science; Engineering; Medicine; Engineering management; Demography; Sociology; Social science; Political science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02094165,0.0006249886,0.0007397149,0.005961272,0.004200867,0.007102015,0.002731689,0.001643392,0.005270651],"category_scores_gemma":[0.1023448,0.0002807043,0.000872415,0.004768354,0.006064456,0.004440468,0.01134614,0.004394232,0.000387108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003019584,"about_ca_system_score_gemma":0.004557191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008781168,"about_ca_topic_score_gemma":0.0167994,"domain_scores_codex":[0.9518056,0.02467142,0.003210272,0.003455626,0.01328395,0.003573221],"domain_scores_gemma":[0.8651108,0.07245662,0.0261512,0.01120384,0.00894597,0.01613166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001323378,0.0007365494,0.94594,0.00007068672,0.000109512,0.0004504562,0.008263378,0.0002378718,0.0001963221,0.004735632,0.0003850267,0.03874221],"study_design_scores_gemma":[0.00001510932,0.0003411276,0.9655712,0.0002310339,0.00003803893,0.0006891243,0.0190581,0.001068563,0.000397424,0.009078688,0.003446458,0.00006529194],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786569,0.001138788,0.003529463,0.004532011,0.0001452099,0.0001123812,0.0001112695,0.00002105313,0.01175284],"genre_scores_gemma":[0.9979681,0.0001099378,0.0007279705,0.0002516835,0.00008565748,0.00004202481,0.00004960383,0.00001241465,0.0007526045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02094165,"threshold_uncertainty_score":0.1107513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03578118444911371,"score_gpt":0.3137613009392732,"score_spread":0.2779801164901595,"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."}}