{"id":"W2886971758","doi":"10.24908/pceea.v0i0.10380","title":"DESCRIBING AND MEASURING THE ENGINEERING KNOWLEDGE BASED USING CONCEPT DOMAINS","year":2018,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Engineering Education and Pedagogy","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Knowledge base; Property (philosophy); Graduation (instrument); Computer science; Base (topology); Curriculum; Computation; Subject (documents); Concept inventory; Concept map; Knowledge management; Mathematics education; Data science; Artificial intelligence; Mathematics; Epistemology; Algorithm; Psychology","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":[0.008421976,0.000477389,0.0003656735,0.01197393,0.000782581,0.005620018,0.001355404,0.0009001915,0.00301925],"category_scores_gemma":[0.05469812,0.0003325824,0.0006334607,0.007180563,0.001640661,0.007193781,0.003536207,0.001529048,0.0005729279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001792386,"about_ca_system_score_gemma":0.001620851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003949205,"about_ca_topic_score_gemma":0.002877444,"domain_scores_codex":[0.9897569,0.003793514,0.0008156753,0.00073591,0.004614314,0.0002837411],"domain_scores_gemma":[0.9289078,0.05174582,0.005561932,0.004945694,0.007878077,0.0009605524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002949708,0.001093812,0.4166148,0.001006543,0.0004078039,0.0003195351,0.008616501,0.03824138,0.009871861,0.09652979,0.003506574,0.4234963],"study_design_scores_gemma":[0.0000695197,0.0007198866,0.4604865,0.001591317,0.0003353475,0.0007906362,0.01583924,0.2705572,0.03243291,0.158206,0.05856803,0.0004034394],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7260078,0.0006616717,0.2188714,0.0007749478,0.0000468408,0.000848104,0.002886442,0.0003773687,0.04952543],"genre_scores_gemma":[0.9079216,0.0002112983,0.08891882,0.00008010499,0.00001325726,0.0003961911,0.001555642,0.00003048171,0.0008727071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01197393,"threshold_uncertainty_score":0.04454017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02099821167028298,"score_gpt":0.2249554207762429,"score_spread":0.2039572091059599,"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."}}