{"id":"W3105029984","doi":"10.1061/9780784482865.112","title":"Implementation of Building Information Modeling on Construction Site: Addressing the Technology Gap","year":2020,"lang":"en","type":"article","venue":"Construction Research Congress 2020","topic":"BIM and Construction Integration","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Building information modeling; Computer science; Virtual reality; Visualization; Leverage (statistics); Field (mathematics); Human–computer interaction; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003767448,0.000177921,0.0002084184,0.0004503408,0.0003704548,0.0001610961,0.0002335298,0.0001781083,0.0002584723],"category_scores_gemma":[0.0001881342,0.000155527,0.00006881898,0.001375861,0.0005145314,0.0007664714,0.00006461779,0.000742386,0.00004611797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001198574,"about_ca_system_score_gemma":0.0001186341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003668812,"about_ca_topic_score_gemma":0.00001484901,"domain_scores_codex":[0.9981104,0.0001309606,0.0005986922,0.0002196994,0.0006149016,0.0003254211],"domain_scores_gemma":[0.9986891,0.00009608858,0.0001348675,0.0002410514,0.0007355629,0.0001033242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001171746,0.000008387703,0.004780346,0.0002606602,0.0001249358,0.000002725707,0.001112153,0.04858999,0.02708896,0.1266903,0.002411908,0.7888125],"study_design_scores_gemma":[0.001576163,0.0002572922,0.000233107,0.000241366,0.00004778073,0.0001587029,0.03158519,0.829145,0.1203121,0.006288635,0.009699982,0.0004547911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8775529,0.0003351553,0.1099665,0.005275517,0.002035375,0.0009604294,0.00008814564,0.000661721,0.003124261],"genre_scores_gemma":[0.9964253,0.0001539827,0.003022436,0.00006852878,0.0002052455,0.00007365349,0.00002899482,0.00001939591,0.000002437028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7883577,"threshold_uncertainty_score":0.6342205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07878585115898361,"score_gpt":0.3558098308802662,"score_spread":0.2770239797212826,"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."}}