{"id":"W4320525624","doi":"10.1016/j.enbuild.2023.112806","title":"Estimating energy savings from HVAC controls fault correction through inverse greybox model-based virtual metering","year":2023,"lang":"en","type":"article","venue":"Energy and Buildings","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; Carleton University","funders":"National Research Council Canada","keywords":"HVAC; Fault detection and isolation; Fault (geology); Engineering; Variable air volume; Simulation; Automotive engineering; Air conditioning; Mechanical engineering; Electrical engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001153824,0.0002910174,0.0002830712,0.0001635665,0.0002538917,0.0001043614,0.0001514935,0.0002141548,0.00002110135],"category_scores_gemma":[0.00004151429,0.0003111245,0.00008262836,0.0004126519,0.00005130939,0.000460033,0.00006518525,0.0001423656,0.000001793137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006709631,"about_ca_system_score_gemma":0.00002011997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006963947,"about_ca_topic_score_gemma":0.0001158283,"domain_scores_codex":[0.9987522,0.00002629881,0.0002982259,0.0003655797,0.0001919391,0.000365768],"domain_scores_gemma":[0.9994517,0.0001408722,0.00007528644,0.0002012047,0.00003871105,0.00009224082],"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":[0.00002417768,0.000009244088,0.00004953087,0.00001095747,0.00004945036,0.000006155406,0.0001630968,0.970192,0.01035696,0.004289198,0.002561887,0.01228736],"study_design_scores_gemma":[0.0005321336,0.00003831858,0.00001534935,0.0001041223,0.00003585688,0.000003503866,0.00003803729,0.9769721,0.0148249,0.003152313,0.003931607,0.0003517248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2968169,0.0001192585,0.7001409,0.00004243835,0.001139385,0.00002716713,0.000009326908,0.00106726,0.0006374031],"genre_scores_gemma":[0.9749369,0.0001688245,0.02343288,0.0003751401,0.0002405241,0.00005495762,0.0001466172,0.00007708032,0.000567064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6781201,"threshold_uncertainty_score":0.9999341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009636560568792146,"score_gpt":0.204336836927691,"score_spread":0.1947002763588988,"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."}}