{"id":"W3033137003","doi":"10.1016/j.enbuild.2020.110192","title":"Intelligent buildings: An overview","year":2020,"lang":"en","type":"article","venue":"Energy and Buildings","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":125,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Energy consumption; Architectural engineering; Productivity; Building automation; Control (management); Computer science; Environmental quality; Engineering; Artificial intelligence","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":[0.0006418047,0.001883262,0.00132179,0.003976902,0.000460427,0.004855461,0.001133236,0.002835399,0.005237806],"category_scores_gemma":[0.0006402966,0.0009604617,0.0008697051,0.006854624,0.0008850679,0.005441843,0.001928123,0.00209738,0.003676858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001218861,"about_ca_system_score_gemma":0.001000251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001632246,"about_ca_topic_score_gemma":0.003058612,"domain_scores_codex":[0.999318,0.0001143902,0.00006148275,0.000150268,0.0002792438,0.00007667224],"domain_scores_gemma":[0.9995438,0.0001671952,0.00005029017,0.00002784169,0.0001524941,0.00005834313],"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":[0.00006498931,0.0002730644,0.000993151,0.00677713,0.00008853655,0.0001809525,0.0001966117,0.007397351,0.001353917,0.06911615,0.05498033,0.8585778],"study_design_scores_gemma":[0.000008271684,0.0001234724,0.001869929,0.002636134,0.00007131798,0.0008366068,0.0002355962,0.003746315,0.000427637,0.01891096,0.9710861,0.00004759794],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000934439,0.9562234,0.01431978,0.001169972,0.00106152,0.00003300959,0.00008820069,0.0001264335,0.02604324],"genre_scores_gemma":[0.01223784,0.964316,0.009502089,0.0008192082,0.002493131,0.0000424591,0.0002072569,0.00004974663,0.01033232],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005237806,"threshold_uncertainty_score":0.01752228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02430214141333579,"score_gpt":0.2260158296601475,"score_spread":0.2017136882468117,"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."}}