{"id":"W2591650844","doi":"10.24908/pceea.v0i0.6500","title":"SLICING AND DICING COMMUNITY ENGAGED LEARNING IN ENGINEERING EDUCATION","year":2017,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Suncor Energy Incorporated","keywords":"Service-learning; Learning community; Experiential learning; Active learning (machine learning); Community engagement; Terminology; Scope (computer science); Pedagogy; Sociology; Public relations; Political science; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001491638,0.0002135954,0.0002274243,0.0004444003,0.0008270222,0.0002310591,0.000423811,0.0002194897,0.000007161572],"category_scores_gemma":[0.004067359,0.0002309169,0.00005340008,0.0003061524,0.00002726061,0.0004419345,0.00005102567,0.001726125,0.000003102966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001719617,"about_ca_system_score_gemma":0.0003495254,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01385143,"about_ca_topic_score_gemma":0.004448882,"domain_scores_codex":[0.9988636,0.00002504031,0.0003396462,0.0001595408,0.0002318931,0.0003802598],"domain_scores_gemma":[0.9990069,0.0001599378,0.0001988345,0.0002038808,0.0001904738,0.0002400073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006770273,0.0003039274,0.8058914,0.01007281,0.0002939604,3.765684e-7,0.02573942,0.04351299,0.05801137,0.007871944,0.01240262,0.03589245],"study_design_scores_gemma":[0.0002516707,0.00001487783,0.9407736,0.001205418,0.00003942085,0.000008017322,0.001431516,0.04562498,0.002351091,0.0001229613,0.007737026,0.0004393894],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931478,0.000247467,0.00004521618,0.001419779,0.002282226,0.0002530737,0.000004061553,0.000190442,0.002409971],"genre_scores_gemma":[0.9984742,0.0000453077,0.0005950173,0.00005637817,0.0002337459,0.00006333199,0.000008775355,0.00005402272,0.0004691833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1348822,"threshold_uncertainty_score":0.9927154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007567841300335522,"score_gpt":0.2014407636152322,"score_spread":0.1938729223148966,"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."}}