{"id":"W4200190812","doi":"10.3390/su14010288","title":"Bim Machine Learning and Design Rules to Improve the Assembly Time in Steel Construction Projects","year":2021,"lang":"en","type":"article","venue":"Sustainability","topic":"BIM and Construction Integration","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Building information modeling; Duration (music); Parametric statistics; Camber (aerodynamics); Engineering; Construction engineering; Computer science; Manufacturing engineering; Industrial engineering; Systems engineering; Operations management; Structural engineering","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":[0.005157981,0.0006489773,0.0006099481,0.002293149,0.0006165122,0.001660673,0.001214163,0.0007045527,0.001833795],"category_scores_gemma":[0.01876089,0.0005130757,0.0004797477,0.00292474,0.0006843964,0.001827605,0.0009808177,0.0006995514,0.0004101667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00201632,"about_ca_system_score_gemma":0.002488998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007295342,"about_ca_topic_score_gemma":0.01156756,"domain_scores_codex":[0.996079,0.002003238,0.0003207933,0.0004440622,0.0009809462,0.0001719551],"domain_scores_gemma":[0.9919532,0.005097989,0.001133836,0.0006591678,0.001051896,0.000103907],"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":[0.0002952239,0.0008275975,0.03916755,0.0003650095,0.00007611954,0.0001555989,0.0018536,0.4986718,0.00397691,0.01358901,0.001831304,0.4391903],"study_design_scores_gemma":[0.00002320735,0.0002243501,0.01959015,0.0001100297,0.00004614422,0.00007652261,0.001170319,0.9578721,0.007138868,0.008644764,0.005061339,0.00004216777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5940554,0.0003556941,0.385352,0.0005078528,0.00002602222,0.0002504123,0.0005490711,0.0008281157,0.01807552],"genre_scores_gemma":[0.827445,0.0001471908,0.1705144,0.00003170902,0.000004270687,0.0001295263,0.0004529445,0.00005824056,0.001216835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007295342,"threshold_uncertainty_score":0.0272783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00610832271846377,"score_gpt":0.2194203811908468,"score_spread":0.213312058472383,"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."}}