{"id":"W2333224724","doi":"10.1061/40558(2001)151","title":"Conceptual Design using Adaptive Search","year":2001,"lang":"en","type":"article","venue":"","topic":"Architecture and Computational Design","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Conceptual design; Revenue; Computer science; Architectural design; Architecture; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001098492,0.0006112141,0.0007753726,0.0009213937,0.0004398933,0.0007852288,0.001261373,0.0007502504,0.00728598],"category_scores_gemma":[0.004221822,0.0004346753,0.0008280792,0.0006800849,0.0007983141,0.000846542,0.001299934,0.0007908432,0.0006527988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00067367,"about_ca_system_score_gemma":0.0008840043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002399638,"about_ca_topic_score_gemma":0.003334226,"domain_scores_codex":[0.9993953,0.0002792997,0.00002418559,0.00007611289,0.0001858968,0.00003930478],"domain_scores_gemma":[0.9987522,0.0008741851,0.00006924609,0.0001430547,0.0001309491,0.00003028625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006248371,0.00004274923,0.0004162422,0.00009580694,0.00003358768,0.00006542245,0.00009627057,0.874513,0.00124467,0.05991111,0.001058101,0.06246048],"study_design_scores_gemma":[0.00002283399,0.00002697441,0.00005268054,0.000008978057,0.000007726177,0.00002083457,0.00001643753,0.981265,0.000293332,0.01669084,0.001589443,0.000004816031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01010285,0.00004970286,0.9842229,0.00007232351,0.00001024925,0.00007685688,0.00003230392,0.0002755789,0.005157153],"genre_scores_gemma":[0.2385608,0.0001126854,0.7585146,0.00007588168,0.00001588285,0.0004571727,0.0001352201,0.0001158072,0.00201199],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00728598,"threshold_uncertainty_score":0.02437407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08540620375173841,"score_gpt":0.2534399128711647,"score_spread":0.1680337091194263,"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."}}