{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007052129,0.0004367501,0.0003027136,0.00214265,0.0037824,0.007274889,0.0009709492,0.001540972,0.002438247],"category_scores_gemma":[0.006405198,0.0002955271,0.0003435472,0.0008529847,0.006575743,0.004239354,0.00844885,0.003753138,0.0006872896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005047339,"about_ca_system_score_gemma":0.02163626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005534716,"about_ca_topic_score_gemma":0.0121142,"domain_scores_codex":[0.9964235,0.001556584,0.0001252279,0.0003010278,0.0009824288,0.0006112017],"domain_scores_gemma":[0.9951088,0.001271762,0.0004062297,0.0002378681,0.0007584862,0.002216934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003821832,0.001320241,0.02014643,0.0007751066,0.00001954657,0.0006751818,0.07342169,0.002240893,0.009869082,0.3696032,0.01268705,0.5092034],"study_design_scores_gemma":[0.0000639771,0.0006082265,0.06554317,0.003188853,0.00003088768,0.0008042364,0.06675315,0.004472745,0.007780185,0.4358464,0.414759,0.0001493504],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.3925814,0.005574613,0.1798666,0.07421328,0.001168079,0.0006640101,0.00007507397,0.0004645734,0.3453925],"genre_scores_gemma":[0.8397532,0.002338491,0.1333598,0.007093693,0.0001407918,0.0003585504,0.0001080947,0.0000671299,0.01678028],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.007274889,"threshold_uncertainty_score":0.03729564,"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."}}