{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02674646,0.000714952,0.0007140124,0.01040461,0.004682465,0.008995859,0.001492502,0.002172447,0.003645777],"category_scores_gemma":[0.04538902,0.0003934103,0.0008710917,0.009097838,0.01442174,0.01385411,0.007544381,0.002767551,0.0004710394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009151077,"about_ca_system_score_gemma":0.01031713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01077641,"about_ca_topic_score_gemma":0.0281252,"domain_scores_codex":[0.9697133,0.01936831,0.002239453,0.00144738,0.006477746,0.0007537653],"domain_scores_gemma":[0.959739,0.02858086,0.002668338,0.003286228,0.00505239,0.0006732178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007864541,0.0000513071,0.004672152,0.006941321,0.00005545927,0.0003535842,0.05731767,0.0009793229,0.001181696,0.3693801,0.01185369,0.5471352],"study_design_scores_gemma":[0.00003635097,0.0003331402,0.01022568,0.02618263,0.0001623871,0.001167457,0.1101346,0.002613493,0.00464889,0.3174214,0.5268964,0.0001776318],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.130147,0.2469564,0.2623558,0.05277691,0.005303341,0.002917337,0.0006500803,0.0004395342,0.2984536],"genre_scores_gemma":[0.7038788,0.08179677,0.1858956,0.008495204,0.000648821,0.001729082,0.0004107824,0.0002544824,0.0168905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02674646,"threshold_uncertainty_score":0.1414505,"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."}}