{"id":"W1902602028","doi":"10.24908/pceea.v0i0.3819","title":"CENTRALIZING INFORMATION IN ENGINEERING DESIGN DOCUMENTS","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Design Education and Practice","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Optimal distinctiveness theory; Computer science; Information design; Engineering ethics; Engineering; Human–computer interaction; 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":[0.0005647694,0.0001649002,0.0001408865,0.0005305725,0.00006062441,0.0001043734,0.0002801774,0.0001467037,0.00007565577],"category_scores_gemma":[0.0006322604,0.0001825206,0.00005097788,0.0007074727,0.000005828785,0.001267888,0.00001213818,0.0002754872,0.00003540064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002183096,"about_ca_system_score_gemma":0.0003264935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003943368,"about_ca_topic_score_gemma":0.0006377243,"domain_scores_codex":[0.9988997,0.000007706231,0.0003843178,0.0001020549,0.0002433529,0.000362857],"domain_scores_gemma":[0.9992622,0.00005255127,0.000178518,0.00009532841,0.0002312554,0.0001802036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004504898,0.000530866,0.315238,0.003908523,0.000845432,0.000001056444,0.07190822,0.2708448,0.01823143,0.06294603,0.2343477,0.02115281],"study_design_scores_gemma":[0.001192008,0.00004993538,0.5565981,0.0009564635,0.0001682609,0.00002245813,0.002365519,0.1289866,0.03657179,0.0007568016,0.2705469,0.00178513],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7346621,0.001111098,0.009646101,0.005300984,0.03332205,0.00598987,0.00009162522,0.002297638,0.2075785],"genre_scores_gemma":[0.994683,0.00002805346,0.004739768,0.0001345428,0.00006771699,0.00007603725,0.00000603992,0.00003220093,0.0002326707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2600209,"threshold_uncertainty_score":0.7442976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01145944405040281,"score_gpt":0.1916066264656655,"score_spread":0.1801471824152626,"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."}}