{"id":"W4313891040","doi":"10.3390/buildings13010163","title":"Digital Technologies in Offsite and Prefabricated Construction: Theories and Applications","year":2023,"lang":"en","type":"article","venue":"Buildings","topic":"BIM and Construction Integration","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Emerging technologies; Current (fluid); Focus (optics); Computer science; Prefabrication; Architectural engineering; Digital transformation; Construction engineering; Construction industry; Systems engineering; Engineering; Manufacturing engineering; Civil engineering; World Wide Web; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009325902,0.0006133401,0.0005989302,0.0050378,0.0008160772,0.004095306,0.0008028096,0.001390744,0.006064045],"category_scores_gemma":[0.001520647,0.000291459,0.0006387651,0.006680237,0.003219332,0.00497782,0.001699254,0.00146882,0.0008821767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001840406,"about_ca_system_score_gemma":0.002185242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001958275,"about_ca_topic_score_gemma":0.002428582,"domain_scores_codex":[0.9993109,0.0001745372,0.00006176575,0.0001026241,0.0002842604,0.00006609073],"domain_scores_gemma":[0.9988236,0.0007800834,0.0001121605,0.00005551718,0.0001866945,0.00004194155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003077688,0.000108694,0.003045671,0.007006894,0.00006438852,0.000556448,0.00330546,0.00159876,0.000866128,0.4722367,0.006669445,0.5045106],"study_design_scores_gemma":[0.00001130047,0.000120209,0.00893347,0.01379596,0.000134955,0.002281629,0.008225923,0.002311623,0.001992762,0.2168745,0.7452341,0.00008346813],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01657876,0.7875654,0.02061338,0.00571386,0.0008608504,0.00009816964,0.0001632483,0.00005847712,0.1683478],"genre_scores_gemma":[0.1263046,0.8503293,0.01150929,0.0009956617,0.000501916,0.00009971607,0.0001540677,0.00001931461,0.01008609],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006064045,"threshold_uncertainty_score":0.02028632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004467769802596306,"score_gpt":0.1926671599167404,"score_spread":0.188199390114144,"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."}}