{"id":"W4411169691","doi":"10.1177/01436244251339726","title":"Deriving optimal direct load control sequences for HVAC systems of small commercial buildings","year":2025,"lang":"en","type":"article","venue":"Building Services Engineering Research and Technology","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Carleton University","funders":"National Research Council Canada","keywords":"HVAC; Automotive engineering; Environmental science; Computer science; Control (management); Engineering; Control theory (sociology); Architectural engineering; Mechanical engineering; Air conditioning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0003807286,0.0008287691,0.0005024406,0.0004499262,0.0003666297,0.0005096758,0.0004410282,0.0005465634,0.001393305],"category_scores_gemma":[0.001209435,0.0004156859,0.0004129851,0.000303567,0.000375856,0.0003721094,0.0003980131,0.0004984093,0.0001084298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001227607,"about_ca_system_score_gemma":0.00139068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02477122,"about_ca_topic_score_gemma":0.02666497,"domain_scores_codex":[0.9998565,0.00003774873,0.000006734978,0.00002991772,0.00003361717,0.00003544093],"domain_scores_gemma":[0.999634,0.0001934849,0.00006363695,0.00001836769,0.00006287439,0.00002750118],"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":[0.00002528319,0.00002527953,0.000419962,0.00001969771,0.000005476777,0.00001784308,0.00001830514,0.9903786,0.001144237,0.0003101813,0.00006850083,0.00756655],"study_design_scores_gemma":[0.000007478941,0.00004395673,0.000245732,0.000002380404,0.000004727132,0.000004366774,0.0000229249,0.9986581,0.0006507885,0.0002427596,0.0001138709,0.000002922161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5983884,0.0002851059,0.3916289,0.0001436631,0.00002608526,0.0002147941,0.00016175,0.0003324232,0.008818832],"genre_scores_gemma":[0.9672453,0.00004405771,0.03181845,0.00001436955,0.000003212928,0.00005292005,0.00008323802,0.00002267449,0.0007157795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02477122,"threshold_uncertainty_score":0.04925406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01039303384298787,"score_gpt":0.2535428111006971,"score_spread":0.2431497772577092,"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."}}