{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001454284,0.0005485407,0.0004025359,0.001321312,0.0002798674,0.001120306,0.0007150062,0.0003614163,0.0007901757],"category_scores_gemma":[0.005723611,0.0002177141,0.0007581313,0.001240297,0.0005241683,0.001399046,0.0007215202,0.0007102533,0.0001523628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005031816,"about_ca_system_score_gemma":0.0004661613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002307576,"about_ca_topic_score_gemma":0.001643428,"domain_scores_codex":[0.9986126,0.0006062256,0.00008186388,0.0002244287,0.0004115289,0.00006321807],"domain_scores_gemma":[0.9980816,0.00110474,0.000231952,0.0002164529,0.000323202,0.00004225667],"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":[0.0002703431,0.00004591213,0.005214746,0.0002337368,0.0001075305,0.00007912565,0.0003784944,0.7210811,0.01499435,0.0416725,0.0003910127,0.2155311],"study_design_scores_gemma":[0.000006987067,0.0000709179,0.001886494,0.00001881761,0.00001744786,0.00004985212,0.00006200286,0.9795701,0.006833213,0.01001591,0.001426103,0.00004227728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02314219,0.0001285308,0.9755998,0.00001746,0.0000173681,0.00001693094,0.00003480592,0.00009127638,0.000951677],"genre_scores_gemma":[0.6283437,0.0002404707,0.3705275,0.00001348668,0.00002838158,0.00006660439,0.0001009336,0.00003791571,0.00064097],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002307576,"threshold_uncertainty_score":0.007691026,"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."}}