{"id":"W3036758339","doi":"10.24908/pceea.vi0.14168","title":"WHAT IS ENGINEERING SCIENCE? DEFINING A DISCIPLINE THROUGH A CROSS-INSTITUTIONAL COMPARISON AND A MULTI-INSTITUTIONAL WORKSHOP","year":2020,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto; Eli and Edythe Broad Foundation","keywords":"Curriculum; Discipline; Engineering ethics; Diversity (politics); Documentation; Multidisciplinary approach; Plan (archaeology); Globe; Process (computing); Cross disciplinary; Sociology; Mathematics education; Engineering; Pedagogy; Computer science; Psychology; Data science; Social science","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0003220307,0.0002568712,0.0002483618,0.0002478796,0.0003544856,0.0004514872,0.0003713206,0.0001880206,0.00002149143],"category_scores_gemma":[0.0009055267,0.0002448551,0.00008066793,0.001228953,0.0001241896,0.001251313,0.00006402246,0.0004185989,0.00001268649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001666877,"about_ca_system_score_gemma":0.000760704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003272166,"about_ca_topic_score_gemma":0.0001758722,"domain_scores_codex":[0.9983025,0.000002061658,0.0004104988,0.0003122758,0.0005160171,0.0004566506],"domain_scores_gemma":[0.9989155,0.00004770295,0.0001232328,0.00009533198,0.0003610285,0.0004572172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002389877,0.0004439422,0.1700265,0.00751834,0.0008010653,0.000001463906,0.05897786,0.5837775,0.0455355,0.07998191,0.04081433,0.01209776],"study_design_scores_gemma":[0.0005853538,0.00001995245,0.1362769,0.0008430077,0.00007400259,0.00001645862,0.0008680666,0.8203113,0.005781717,0.00009408113,0.03440025,0.0007289157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9684139,0.002733923,0.003211516,0.01588123,0.007765255,0.0006158539,0.00008380094,0.0005886208,0.0007058953],"genre_scores_gemma":[0.9918364,0.00008271491,0.007179807,0.000365965,0.000306269,0.00005635328,0.00001897552,0.00003681661,0.0001167074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2365339,"threshold_uncertainty_score":0.9984901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01682861946453862,"score_gpt":0.257813209876518,"score_spread":0.2409845904119793,"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."}}