{"id":"W4313201678","doi":"10.1016/j.cscm.2022.e01755","title":"Bim-based energy analysis and optimization using insight 360 (case study)","year":2022,"lang":"en","type":"article","venue":"Case Studies in Construction Materials","topic":"BIM and Construction Integration","field":"Engineering","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"Abbott (Canada)","funders":"King Khalid University; Najran University; Deanship of Scientific Research, King Faisal University","keywords":"Building information modeling; Energy consumption; Sustainability; Environmental economics; Energy management; Energy modeling; Consumption (sociology); Efficient energy use; Engineering; Green building; Civil engineering; Energy (signal processing); Architectural engineering; Environmental resource management; Operations management; Environmental science; Economics","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":[0.0002287311,0.0001740891,0.0003436676,0.0006917921,0.0003969577,0.00006399884,0.00003276507,0.0000434385,0.0003898497],"category_scores_gemma":[0.0000222265,0.0001863177,0.00003963427,0.0009736453,0.0001532019,0.0001564046,0.00006058464,0.00007845034,2.444028e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001967398,"about_ca_system_score_gemma":0.00002000127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003254304,"about_ca_topic_score_gemma":0.0002837509,"domain_scores_codex":[0.9988113,0.0002258811,0.0004531896,0.0002483123,0.0001228005,0.0001384865],"domain_scores_gemma":[0.9995706,0.00005449064,0.00009494823,0.0001623583,0.00008521628,0.00003235806],"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":[0.00003123276,0.00003290691,0.003247622,0.00004897858,0.0006853956,0.004977582,0.001064418,0.9830738,0.001310389,0.000884656,0.0000189463,0.004624045],"study_design_scores_gemma":[0.004079923,0.000272137,0.000097359,0.00005355828,0.002468211,0.1370132,0.1832479,0.6518254,0.0181888,0.0007066973,0.0005853926,0.001461472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618066,0.0005042963,0.03560703,0.000006766171,0.001674677,0.0001707629,0.00005299896,0.0001275511,0.00004932281],"genre_scores_gemma":[0.9916073,0.00006447089,0.008080627,0.00001766454,0.00006145657,0.0001315296,0.00001429698,0.00001805015,0.000004609694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3312485,"threshold_uncertainty_score":0.7597814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02881465003547695,"score_gpt":0.2713294658113661,"score_spread":0.2425148157758891,"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."}}