{"id":"W2909708433","doi":"10.24908/pceea.v0i0.12972","title":"Knowledge structures in engineering design: integrating multiple ‘ways of knowing’","year":2018,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Design Education and Practice","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Cape Town","keywords":"Computer science; Focus (optics); Inference; Engineering design process; Design knowledge; Modalities; Knowledge engineering; Management science; Artificial intelligence; Cognitive science; Engineering; Sociology; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006302224,0.0001935171,0.0002155454,0.0005635412,0.00007753313,0.00006679486,0.0003384097,0.0001992661,0.00003822642],"category_scores_gemma":[0.002854528,0.0002029083,0.00006797769,0.0009801957,0.00002019852,0.0003385866,0.00001777633,0.000389529,0.000009681248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001550467,"about_ca_system_score_gemma":0.0005034388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00199948,"about_ca_topic_score_gemma":0.002671567,"domain_scores_codex":[0.9988417,0.00001110678,0.0004298295,0.0001630191,0.0002087608,0.0003455778],"domain_scores_gemma":[0.9987075,0.0002514955,0.000212882,0.0001220825,0.0005738576,0.0001322201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003321489,0.0004195464,0.1728985,0.00445787,0.0008029276,7.091181e-7,0.05662834,0.1077017,0.2862166,0.0668146,0.2858686,0.01815754],"study_design_scores_gemma":[0.001014481,0.000105466,0.2119684,0.001311139,0.000155521,0.00001889045,0.002472331,0.4049192,0.2016258,0.0009877145,0.1739182,0.001502787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9028416,0.001536876,0.01054088,0.01009591,0.01900223,0.003225231,0.00007095813,0.001111797,0.05157455],"genre_scores_gemma":[0.9917135,0.000006862552,0.007477017,0.0001522685,0.0003268098,0.00004412631,0.000003475905,0.00005153323,0.0002244276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2972176,"threshold_uncertainty_score":0.827436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01880731440976187,"score_gpt":0.2302005727717877,"score_spread":0.2113932583620259,"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."}}