{"id":"W4391131361","doi":"10.3390/en17030555","title":"Energy Management in Modern Buildings Based on Demand Prediction and Machine Learning—A Review","year":2024,"lang":"en","type":"article","venue":"Energies","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Energy (signal processing); Energy management; Energy demand; Architectural engineering; Computer science; Engineering; Environmental economics; Economics","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":[0.0005674141,0.000878586,0.001134928,0.001353496,0.0002056787,0.0009640023,0.0007957228,0.0008833446,0.001431124],"category_scores_gemma":[0.0006952046,0.0002928704,0.0005651289,0.002445695,0.0003207936,0.001382591,0.0004675138,0.0006435147,0.0005737886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003876294,"about_ca_system_score_gemma":0.0007749976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001727263,"about_ca_topic_score_gemma":0.002054364,"domain_scores_codex":[0.9997465,0.00004319172,0.00003226455,0.00004945659,0.0001091924,0.00001934064],"domain_scores_gemma":[0.9995983,0.0002405887,0.00005094592,0.00001031362,0.00008572404,0.00001410909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004400059,0.000125998,0.0007638811,0.01770362,0.0001209943,0.00009733105,0.00005402064,0.01008114,0.001315944,0.007893414,0.009622014,0.9521776],"study_design_scores_gemma":[0.00002931943,0.000588359,0.005947408,0.01545573,0.0006317304,0.001123591,0.0003697141,0.01629828,0.003231437,0.016767,0.9394046,0.0001528161],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0009144726,0.9941391,0.002828819,0.0002994813,0.0001573375,0.00001126816,0.0000278483,0.00001930651,0.001602391],"genre_scores_gemma":[0.006453793,0.9910073,0.001791345,0.00008589351,0.0002675428,0.00001135739,0.00005214626,0.000004282223,0.0003263664],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.001727263,"threshold_uncertainty_score":0.004787624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005696481590750649,"score_gpt":0.1882687450794918,"score_spread":0.1825722634887412,"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."}}