{"id":"W4399043571","doi":"10.22260/isarc2024/0174","title":"Analysis of openBIM Adoptions and Implementations: Global Perspectives and Canadian Industry Adoption","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... ISARC","topic":"BIM and Construction Integration","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Implementation; Computer science; Telecommunications; Data science; Business; Software engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.00976138,0.0005605274,0.000499526,0.009623713,0.007075668,0.008388664,0.00204141,0.0008893945,0.003332568],"category_scores_gemma":[0.02249329,0.0004336372,0.0006633938,0.02842357,0.004715004,0.003670873,0.006530529,0.001648624,0.000262548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07914398,"about_ca_system_score_gemma":0.08784861,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.95932,"about_ca_topic_score_gemma":0.9665737,"domain_scores_codex":[0.9866583,0.001397317,0.0004812039,0.001066662,0.007157781,0.003238738],"domain_scores_gemma":[0.9824319,0.002924294,0.001809146,0.0009527701,0.01030494,0.001576897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002151845,0.0001663861,0.4008464,0.0008186085,0.00009866824,0.0008481393,0.2432043,0.001486461,0.002041037,0.09808643,0.009260484,0.242928],"study_design_scores_gemma":[0.00001905619,0.0001163375,0.6610892,0.0006676161,0.0001014082,0.0002894844,0.2150081,0.001688471,0.001167915,0.00253052,0.1171703,0.0001516226],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.881768,0.001543182,0.001579728,0.004233769,0.00003660419,0.000221208,0.001405671,0.00009866595,0.1091132],"genre_scores_gemma":[0.9891094,0.001971623,0.002280346,0.000273534,0.000006435498,0.00007387794,0.0009108318,0.00004902216,0.005325017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07914398,"threshold_uncertainty_score":0.5742325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009728157840064202,"score_gpt":0.2455020530618391,"score_spread":0.2357738952217749,"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."}}