{"id":"W4220923011","doi":"10.1016/j.apenergy.2022.118651","title":"Automatic dimensioning of energy system components for building cluster simulation","year":2022,"lang":"en","type":"article","venue":"Applied Energy","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Bundesministerium für Wirtschaft und Energie","keywords":"Dimensioning; Boiler (water heating); Genetic algorithm; Heat pump; Electricity; Thermal energy storage; Computer science; Systems design; Process engineering; Automotive engineering; Engineering; Simulation; Reliability engineering; Mechanical engineering; Electrical engineering; Systems engineering; Waste management","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":[0.0002749486,0.0006504838,0.0006794241,0.0005728938,0.0005310395,0.0007697084,0.0007608301,0.0004278812,0.006206002],"category_scores_gemma":[0.001803623,0.0005944035,0.0005550938,0.0004585707,0.0003204764,0.000634221,0.0006952304,0.000889946,0.000644499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005603416,"about_ca_system_score_gemma":0.000861712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009593993,"about_ca_topic_score_gemma":0.0142608,"domain_scores_codex":[0.999818,0.0000484995,0.00001151266,0.0000307395,0.00006530237,0.00002586645],"domain_scores_gemma":[0.9995143,0.0002349597,0.00003248424,0.0001044517,0.00008931042,0.00002437944],"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":[0.0001883317,0.00006490261,0.001584818,0.0001084359,0.0000436554,0.00005542685,0.0001307041,0.8973447,0.008032354,0.004854794,0.002047422,0.08554443],"study_design_scores_gemma":[0.000007814495,0.000006699261,0.0001488139,0.000002403404,0.000002993253,0.000005062131,0.000008399767,0.9964063,0.001699456,0.001107873,0.0006004006,0.000003806803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09261059,0.0001093501,0.8895152,0.0001017458,0.00007411028,0.000118511,0.0005292167,0.01133708,0.005604177],"genre_scores_gemma":[0.7810113,0.00005261946,0.2160262,0.00003441922,0.00001237945,0.0001649338,0.0005376595,0.0007251198,0.001435248],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009593993,"threshold_uncertainty_score":0.02076113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01467940784647971,"score_gpt":0.2289158224742536,"score_spread":0.2142364146277739,"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."}}