{"id":"W2968066111","doi":"10.1007/s12273-019-0558-9","title":"Adaptive modeling for reliability in optimal control of complex HVAC systems","year":2019,"lang":"en","type":"article","venue":"Building Simulation","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"University of Hong Kong; National Center for Theoretical Sciences; City University of Hong Kong","keywords":"HVAC; Reliability (semiconductor); Reliability engineering; Set (abstract data type); Computer science; Air conditioning; Control engineering; Process (computing); Engineering; Power (physics)","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":[0.0006378398,0.0004818818,0.0007010183,0.0003500366,0.0003043605,0.0006030138,0.0007450471,0.0007623764,0.002012928],"category_scores_gemma":[0.002999214,0.0004380013,0.0004915285,0.0002961795,0.0005651989,0.0007318224,0.0006030219,0.0009439987,0.0002022522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005767728,"about_ca_system_score_gemma":0.0007164048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01148221,"about_ca_topic_score_gemma":0.005770072,"domain_scores_codex":[0.9997185,0.0001362614,0.00001087451,0.00003197651,0.00006653636,0.00003588868],"domain_scores_gemma":[0.9991969,0.0005396851,0.00008734736,0.00005260037,0.00009967166,0.00002373246],"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":[0.000007619175,0.00000557703,0.00006194165,0.000006332345,0.000004198717,0.000003969208,0.000008296289,0.9956067,0.0002017383,0.002453906,0.00005481873,0.001584863],"study_design_scores_gemma":[9.784337e-7,0.000002512554,0.00001900092,7.046588e-7,7.664954e-7,6.245884e-7,8.21965e-7,0.9993461,0.00003286253,0.0005594492,0.00003553483,7.085713e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.056997,0.0004170144,0.9357897,0.0003542809,0.0000667652,0.00002993905,0.00006091157,0.0002537583,0.006030617],"genre_scores_gemma":[0.9793012,0.0001998961,0.0179217,0.00003869716,0.00003204835,0.00005630897,0.00003299701,0.00005368067,0.002363402],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01148221,"threshold_uncertainty_score":0.02283072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02059421175022173,"score_gpt":0.244786754909608,"score_spread":0.2241925431593862,"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."}}