{"id":"W2746387342","doi":"","title":"MODELING ENERGY DEMAND FOR HEATING AT CITY SCALE","year":2010,"lang":"en","type":"article","venue":"Proceedings of SimBuild","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Heating system; Work (physics); Energy consumption; Scale (ratio); Energy demand; Quarter (Canadian coin); Energy (signal processing); Consumption (sociology); Computer science; Architectural engineering; Environmental economics; Engineering; Geography; Mechanical engineering; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001421177,0.0003462475,0.0003572428,0.0002642099,0.000236175,0.0007789209,0.0006635838,0.0008397116,0.005853928],"category_scores_gemma":[0.0005470393,0.0003837962,0.0005364275,0.0008029002,0.0002241561,0.0007371005,0.0004215086,0.0005031696,0.0007152502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001077892,"about_ca_system_score_gemma":0.0006395582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0377662,"about_ca_topic_score_gemma":0.03352121,"domain_scores_codex":[0.9999056,0.0000193428,0.000003996357,0.00002745875,0.0000187317,0.0000247791],"domain_scores_gemma":[0.9998435,0.00008019315,0.00001716184,0.00001858673,0.00002494158,0.00001569494],"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":[0.000009869786,0.00001531685,0.001063964,0.000006400882,0.000006713455,0.00002090893,0.000007538329,0.9959259,0.0004570257,0.001452016,0.0001983911,0.0008360494],"study_design_scores_gemma":[0.000002552839,0.000002816088,0.0005894886,6.097318e-7,0.000001828293,0.000003081773,0.000008855895,0.9984952,0.00009058072,0.0005365403,0.000266421,0.000001995462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8521956,0.0002087764,0.1063931,0.0006191463,0.00005550611,0.00005384631,0.003107466,0.0005819607,0.03678465],"genre_scores_gemma":[0.9854674,0.00009249542,0.00593414,0.00002650665,0.00001206885,0.00004443968,0.0006987316,0.00006716356,0.007657076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0377662,"threshold_uncertainty_score":0.07509279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007328764203049188,"score_gpt":0.1956034224058357,"score_spread":0.1882746582027865,"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."}}