{"id":"W4362703390","doi":"10.1016/j.autcon.2023.104859","title":"Dynamic integration of unstructured data with BIM using a no-model approach based on machine learning and concept networks","year":2023,"lang":"en","type":"article","venue":"Automation in Construction","topic":"BIM and Construction Integration","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Unstructured data; Generalizability theory; Classifier (UML); Artificial intelligence; Parametric statistics; Machine learning; Data mining; Data science; Natural language processing; Big data","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":[0.001478352,0.0008559174,0.001296244,0.00172569,0.0007543323,0.002391672,0.001530292,0.0008365972,0.002004517],"category_scores_gemma":[0.005531064,0.0009502514,0.001115155,0.002415039,0.001030993,0.005096691,0.003034336,0.001274408,0.0004276899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001012407,"about_ca_system_score_gemma":0.001333881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0114294,"about_ca_topic_score_gemma":0.01206781,"domain_scores_codex":[0.9987301,0.0003500384,0.00006455828,0.0002985515,0.0004688506,0.00008793233],"domain_scores_gemma":[0.9983788,0.0008213284,0.0001631986,0.000276861,0.0003086069,0.00005125644],"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":[0.00007851781,0.00009914247,0.001474181,0.00009831175,0.00007940843,0.0001580188,0.0001995854,0.8730257,0.002464781,0.03567063,0.000762093,0.08588964],"study_design_scores_gemma":[0.000002044077,0.000009445776,0.0002250943,0.00000613912,0.000009614622,0.0000143846,0.00002571277,0.9892518,0.0006024988,0.009193803,0.0006530066,0.000006451044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01377181,0.0001063018,0.9838809,0.00009781271,0.00003632663,0.00003390823,0.00007507038,0.00026952,0.001728379],"genre_scores_gemma":[0.5352337,0.0003454133,0.4603611,0.00007118031,0.00005790528,0.0001754035,0.000591309,0.0002102266,0.002953707],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0114294,"threshold_uncertainty_score":0.02272576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415341077109038,"score_gpt":0.2392545917782159,"score_spread":0.2251011810071255,"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."}}