{"id":"W3132863246","doi":"10.82308/43228","title":"Model predictive control of electric building energy and heating systems","year":2020,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Model predictive control; Control (management); Energy (signal processing); Environmental science; Computer science; Mathematics; Artificial intelligence; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002577892,0.0003491383,0.0006049313,0.0001578664,0.000227338,0.00003384924,0.0002071651,0.0001986236,0.000002384068],"category_scores_gemma":[0.0003274838,0.0003898478,0.00008741189,0.000479731,0.00002411975,0.0006798454,0.00005400646,0.000312098,0.000002147664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002704191,"about_ca_system_score_gemma":0.00001169053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006073512,"about_ca_topic_score_gemma":0.000005362912,"domain_scores_codex":[0.9979519,0.0001313634,0.0006888024,0.0004446334,0.0003367909,0.0004465109],"domain_scores_gemma":[0.998916,0.0001936941,0.0002038334,0.0002389146,0.0001832793,0.0002643304],"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":[0.00003954491,0.000007619617,0.00002117405,0.0001276853,0.0000962294,0.000003399767,0.00000419889,0.692414,0.2659893,0.03729444,3.627982e-7,0.004002009],"study_design_scores_gemma":[0.00125378,0.0001129989,0.00001141579,0.0001119205,0.00007112137,0.00001328228,0.00003216101,0.9695671,0.02682732,0.001353683,0.0003179679,0.000327265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6437209,0.0061644,0.3280744,0.00003773656,0.0006312365,0.00171401,0.001002726,0.001889766,0.0167649],"genre_scores_gemma":[0.9972811,0.0001137109,0.00222211,0.00008552222,0.00005100988,0.00009994532,0.000007451561,0.0001194867,0.00001961455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3535603,"threshold_uncertainty_score":0.9998553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009468536487499018,"score_gpt":0.1886334192754548,"score_spread":0.1791648827879558,"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."}}