{"id":"W3128026765","doi":"10.1115/1.2164452","title":"Modeling of Evolutionary Design Database","year":2005,"lang":"en","type":"article","venue":"Journal of Computing and Information Science in Engineering","topic":"Design Education and Practice","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Consistency (knowledge bases); Ancestor; Descendant; Database; Generative Design; Database design; Conceptual design; Artificial intelligence; Engineering; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.002819923,0.0007108455,0.000626156,0.002004446,0.0009070021,0.004308185,0.003387535,0.001527302,0.003932972],"category_scores_gemma":[0.006288242,0.0006769848,0.001487658,0.002124038,0.000976985,0.004638864,0.001791376,0.001282253,0.001053104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001739039,"about_ca_system_score_gemma":0.001750602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006390697,"about_ca_topic_score_gemma":0.003648262,"domain_scores_codex":[0.9972103,0.0008656636,0.0003490573,0.0004792492,0.0009308598,0.0001649323],"domain_scores_gemma":[0.9972631,0.0008618702,0.0002810862,0.0008486279,0.00063436,0.0001110687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001471389,0.0001775716,0.003711836,0.0003036367,0.00008310107,0.0009829877,0.001207719,0.3054605,0.00423077,0.5765342,0.003466633,0.1036939],"study_design_scores_gemma":[0.00005985326,0.0001014088,0.000604104,0.0001238425,0.00006903536,0.001100332,0.0002739892,0.7745957,0.003492598,0.1325827,0.08694696,0.00004942164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0145126,0.0004890217,0.9679244,0.0004627949,0.00005337042,0.0001934975,0.0005673071,0.0006689316,0.01512806],"genre_scores_gemma":[0.2420569,0.001118394,0.7402946,0.0002207693,0.00004408476,0.0007084897,0.002381723,0.0001702621,0.01300482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006390697,"threshold_uncertainty_score":0.01491338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02044037714741485,"score_gpt":0.2664097345006112,"score_spread":0.2459693573531963,"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."}}