{"id":"W2930776121","doi":"10.11159/icsect19.134","title":"3D Model Generation of CFS Members from Surface Data","year":2019,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Civil, Structural, and Environmental Engineering","topic":"BIM and Construction Integration","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Computer science; Data modeling; Database","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003624005,0.001174223,0.0008076587,0.001733531,0.0003844069,0.001270006,0.001281367,0.001345822,0.00521738],"category_scores_gemma":[0.00120852,0.0009102178,0.001545659,0.001662635,0.0005189941,0.0006933493,0.001373468,0.0009572164,0.002611438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005543763,"about_ca_system_score_gemma":0.00163373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007675384,"about_ca_topic_score_gemma":0.01168178,"domain_scores_codex":[0.9995502,0.00003214692,0.00002529848,0.00007681391,0.000269354,0.00004622505],"domain_scores_gemma":[0.9995783,0.0001013027,0.00003016538,0.0000914547,0.0001741207,0.00002466847],"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":[0.0002114586,0.0002578183,0.005578689,0.0002895834,0.00007627175,0.0005937963,0.0004862794,0.7213604,0.05112297,0.005332844,0.01384906,0.2008409],"study_design_scores_gemma":[0.00001443842,0.00003589853,0.0009856895,0.00001166603,0.000009499346,0.0000843929,0.0001087982,0.9828938,0.00950308,0.001261603,0.005061865,0.00002936868],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06578761,0.0001108966,0.9091505,0.000206173,0.0001152523,0.000392181,0.00755847,0.01212435,0.004554528],"genre_scores_gemma":[0.4550688,0.0003158156,0.5212147,0.00009630488,0.00003035791,0.0007896299,0.01755007,0.001274931,0.003659255],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007675384,"threshold_uncertainty_score":0.01745385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01138886974548191,"score_gpt":0.1870707467830088,"score_spread":0.1756818770375269,"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."}}