{"id":"W2789738984","doi":"10.3390/buildings8020021","title":"Interval Estimations of Building Heating Energy Consumption using the Degree-Day Method and Fuzzy Numbers","year":2018,"lang":"en","type":"article","venue":"Buildings","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Degree (music); Interval (graph theory); Range (aeronautics); Multiplication (music); Fuzzy logic; Mathematics; Energy (signal processing); Energy consumption; Fuzzy number; Point (geometry); Interval arithmetic; Computer science; Statistics; Arithmetic; Algorithm; Fuzzy set; Mathematical optimization; Artificial intelligence; Engineering; Mathematical analysis","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003640718,0.0001410623,0.0001599345,0.0001043848,0.0002114997,0.00004703925,0.0001301305,0.00008363496,0.00002788877],"category_scores_gemma":[0.00005230061,0.0001234124,0.00004477807,0.0002255343,0.0001208921,0.0002047631,0.00006153181,0.00009746043,3.401938e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004638069,"about_ca_system_score_gemma":0.00001138136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002277981,"about_ca_topic_score_gemma":0.00002610145,"domain_scores_codex":[0.9992197,0.00004867926,0.0002634804,0.0001593614,0.0001193393,0.0001895001],"domain_scores_gemma":[0.9994907,0.0001489686,0.00008273975,0.0001675444,0.00006671866,0.00004333237],"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":[0.000009739091,0.00001251431,0.001455981,0.0000654067,0.00009328659,6.861428e-7,0.0008056781,0.8563054,0.05207124,0.043781,0.0002086777,0.04519038],"study_design_scores_gemma":[0.0001612808,0.00002090445,0.0002148512,0.0001366752,0.0000497669,0.00003368097,0.00004544387,0.9579693,0.03901867,0.00165191,0.000539389,0.0001581362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2964676,0.0001611901,0.7024969,0.00002380826,0.0001969065,0.00003976439,0.000002057247,0.0001132492,0.0004985662],"genre_scores_gemma":[0.7567977,0.0000303606,0.242991,0.00004048963,0.00009137145,0.000006314624,0.000002514234,0.00002485864,0.00001536289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4603301,"threshold_uncertainty_score":0.5032611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03860374652854999,"score_gpt":0.2861594259658543,"score_spread":0.2475556794373043,"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."}}