{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000589636,0.0001745684,0.0001638559,0.00004853644,0.00008597534,0.00006219112,0.0001498876,0.0001019344,0.00009684956],"category_scores_gemma":[0.000009814074,0.0001737833,0.00004087083,0.0002231618,0.00002928164,0.0002796184,0.00004721048,0.00009659676,0.000001838996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001647558,"about_ca_system_score_gemma":0.000006405477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003221022,"about_ca_topic_score_gemma":0.000006352062,"domain_scores_codex":[0.9992661,0.00001349594,0.0001737764,0.0002354483,0.0001050642,0.0002061079],"domain_scores_gemma":[0.9996261,0.00001531267,0.00002422292,0.0001209842,0.00001920709,0.0001941753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002347184,0.00002765812,0.0002062117,0.00009063294,0.00006568058,0.000009643781,0.0005308441,0.6473945,0.005330155,0.2401692,0.004288861,0.1018631],"study_design_scores_gemma":[0.0002661886,0.0001319441,0.00004892945,0.00005749621,0.00003019044,0.00001650308,0.00006322256,0.3222608,0.0314091,0.001912085,0.6432989,0.0005046828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4692093,0.02247626,0.4973871,0.001564972,0.0008581847,0.000133025,0.00001062309,0.002675596,0.005684948],"genre_scores_gemma":[0.9846094,0.00518381,0.007603566,0.002162991,0.0002742168,0.00001295135,0.00002084943,0.00005030318,0.00008195132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.63901,"threshold_uncertainty_score":0.7086677,"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."}}