{"id":"W3036180169","doi":"10.24908/pceea.vi0.14129","title":"BUILDING THE ENGINEERING MINDSET: DEVELOPING LEADERSHIP AND MANAGEMENT COMPETENCIES IN THE ENGINEERING CURRICULUM","year":2020,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Engineering Education and Curriculum Development","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Alberta","funders":"","keywords":"Mindset; Health systems engineering; Competence (human resources); Curriculum; Engineering; Engineering ethics; Engineering management; Engineering education; Management; Computer science; Pedagogy; Sociology","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":[],"consensus_categories":[],"category_scores_codex":[0.0005135229,0.0002994992,0.000220927,0.0002904439,0.0001506922,0.000212545,0.0006204335,0.0001264057,0.0000108248],"category_scores_gemma":[0.0003427462,0.0002379566,0.00007587919,0.001228638,0.00001629244,0.0002147896,0.0000406299,0.0004781417,0.000006494531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001079,"about_ca_system_score_gemma":0.0001445237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004509938,"about_ca_topic_score_gemma":0.0003845809,"domain_scores_codex":[0.9983997,0.000008507571,0.0004240152,0.0002388576,0.0004065288,0.0005223918],"domain_scores_gemma":[0.9993747,0.00008951085,0.0001064803,0.0001317204,0.0001178679,0.0001796473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000005554069,0.0001349861,0.05931337,0.008023162,0.000873894,0.000003558904,0.03824158,0.625419,0.00646064,0.1766817,0.07807255,0.006770043],"study_design_scores_gemma":[0.0006524119,0.00002658676,0.3633766,0.001572014,0.0001738641,0.00004013137,0.007638082,0.3095041,0.002356105,0.0001010735,0.3129271,0.001631982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9409897,0.002216028,0.0007860797,0.04819655,0.003444154,0.002018845,0.00002148639,0.0006440716,0.001683141],"genre_scores_gemma":[0.9931707,0.00009615374,0.005421853,0.0007412129,0.0002109808,0.000208053,0.000005617311,0.000061328,0.00008407136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3159148,"threshold_uncertainty_score":0.9703588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0115136668926809,"score_gpt":0.1888048285966442,"score_spread":0.1772911617039633,"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."}}