{"id":"W2898503720","doi":"10.3390/proceedings2211365","title":"Adapting to Engineering Education Vision 2020","year":2018,"lang":"en","type":"article","venue":"","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Context (archaeology); Multidisciplinary approach; Engineering ethics; Engineering; Sociology; Social science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.02111608,0.00144146,0.0005511259,0.001587718,0.003342402,0.00838182,0.002303796,0.01323188,0.02948069],"category_scores_gemma":[0.01508671,0.0003784755,0.0009954723,0.0006886465,0.004111397,0.007111995,0.01085045,0.01096182,0.01832703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007770051,"about_ca_system_score_gemma":0.04952658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006423965,"about_ca_topic_score_gemma":0.009251832,"domain_scores_codex":[0.9874751,0.003215197,0.0005258808,0.0007716432,0.004679488,0.003332765],"domain_scores_gemma":[0.9833819,0.001498362,0.0004886215,0.0005716123,0.004378132,0.009681483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005061532,0.0003471384,0.0006535657,0.0004360986,0.00001363291,0.0001843042,0.001390842,0.001136435,0.001304134,0.3259662,0.5127393,0.1557778],"study_design_scores_gemma":[0.000009433853,0.00007748529,0.0005820477,0.0002429726,0.000002373162,0.0001022012,0.0008810124,0.0002346754,0.0003070463,0.03133105,0.9662184,0.00001131262],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.005248228,0.006850746,0.02182389,0.5660883,0.02416016,0.0002862517,0.0004750846,0.001001717,0.3740656],"genre_scores_gemma":[0.1225663,0.01212188,0.0805814,0.3765335,0.006617587,0.0009145342,0.001795361,0.0006770768,0.3981923],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02948069,"threshold_uncertainty_score":0.1116738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003376825398323346,"score_gpt":0.2153938509130462,"score_spread":0.2120170255147229,"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."}}