{"id":"W3180630644","doi":"10.1155/2021/6638236","title":"Building Information Modelling‐ (BIM‐) Based Generative Design for Drywall Installation Planning in Prefabricated Construction","year":2021,"lang":"en","type":"article","venue":"Advances in Civil Engineering","topic":"BIM and Construction Integration","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Building information modeling; Construction engineering; Architectural engineering; Computer science; Engineering; Civil engineering; Operations management","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001402419,0.0001606666,0.0001635125,0.0003355324,0.00003566326,0.00005044478,0.00005354139,0.0001043656,0.000007623581],"category_scores_gemma":[0.00006236935,0.000196957,0.00003329222,0.0004953193,0.00001223456,0.001422861,0.000006958603,0.000179154,9.815795e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002317312,"about_ca_system_score_gemma":0.00004186117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003408775,"about_ca_topic_score_gemma":0.00003904794,"domain_scores_codex":[0.9991155,0.00001767489,0.0003962734,0.000149489,0.0001086125,0.000212503],"domain_scores_gemma":[0.9996148,0.000119635,0.00005103775,0.00009549114,0.00008867155,0.00003040758],"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":[0.00001299898,0.000004599849,0.0002700028,0.00009632835,0.00000610795,0.000001237269,0.0001819341,0.9766701,0.002767785,0.007432504,0.000003415655,0.01255303],"study_design_scores_gemma":[0.0005653706,0.00001300293,0.00009847587,0.0001874171,0.000004712338,0.000006610473,0.00009493171,0.9751846,0.0195609,0.001722364,0.002358976,0.0002026308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.019183,0.001020289,0.9783552,0.00001349986,0.0005645934,0.0002469,0.000006747474,0.0002031809,0.0004065815],"genre_scores_gemma":[0.6981869,0.00009621719,0.3014845,0.00001086882,0.00004114331,0.0001175961,0.00004505677,0.00001663656,0.000001098766],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6790039,"threshold_uncertainty_score":0.8031673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01443380167805821,"score_gpt":0.2274941224769639,"score_spread":0.2130603207989057,"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."}}