{"id":"W3042884152","doi":"10.32920/ryerson.14654307.v1","title":"Grey box modelling and advanced control scheme for building heating systems","year":2021,"lang":"en","type":"article","venue":"","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adaptive neuro fuzzy inference system; Computer science; Robustness (evolution); Inference; Heating system; Control engineering; Machine learning; Fuzzy control system; Fuzzy logic; Data mining; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000536486,0.0005636367,0.0006401492,0.0002526127,0.0002803978,0.0007826306,0.0006134239,0.0006853598,0.003265696],"category_scores_gemma":[0.0008757284,0.0002322934,0.0006867658,0.0002915893,0.0005055289,0.0006191863,0.0005449309,0.0007869925,0.000388692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005713323,"about_ca_system_score_gemma":0.0004515981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004207251,"about_ca_topic_score_gemma":0.003044276,"domain_scores_codex":[0.9997895,0.00007386495,0.000009962444,0.00004176033,0.00006628433,0.00001860009],"domain_scores_gemma":[0.9998538,0.0000746779,0.00001962283,0.00001162528,0.00003406635,0.000006020057],"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":[0.00002721922,0.000009258754,0.00008849204,0.00005245821,0.00001682489,0.00003915667,0.00004534121,0.9668772,0.002527268,0.01744506,0.0002109754,0.01266076],"study_design_scores_gemma":[0.000002054421,0.000011045,0.0000292456,0.00000287349,0.000002862716,0.000003594319,0.000002103,0.9975767,0.000230056,0.001782887,0.0003549485,0.000001772135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01574482,0.0003678373,0.9770554,0.000131684,0.00006005941,0.00004090466,0.00003426975,0.0001987542,0.006366336],"genre_scores_gemma":[0.9385605,0.0005486533,0.05128054,0.00004259327,0.00003132298,0.0001430084,0.00006736026,0.00003081167,0.009295183],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004207251,"threshold_uncertainty_score":0.01092488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00963129317637517,"score_gpt":0.2038876757990074,"score_spread":0.1942563826226323,"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."}}