{"id":"W4380986481","doi":"10.1051/e3sconf/202339604005","title":"Dynamic simulation of a hydrogen-fueled system for zero-energy buildings using TRNSYS software","year":2023,"lang":"en","type":"article","venue":"E3S Web of Conferences","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"TRNSYS; Renewable energy; Environmental science; Zero-energy building; Energy storage; Automotive engineering; Process engineering; Engineering; Energy (signal processing); Power (physics); Electrical engineering","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004608732,0.0002753173,0.0007518148,0.0004605376,0.0001076111,0.00003294366,0.0003898925,0.0001843466,0.00003482201],"category_scores_gemma":[0.0002085197,0.0002577947,0.0002342187,0.0006923212,0.0001074628,0.0001615355,0.00007174052,0.00005458821,0.000006068132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001006219,"about_ca_system_score_gemma":0.0007053422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005167576,"about_ca_topic_score_gemma":0.0008023517,"domain_scores_codex":[0.9976801,0.0001461175,0.0009063462,0.0004037439,0.000458121,0.0004055258],"domain_scores_gemma":[0.9979046,0.0005490075,0.0006643932,0.0003973532,0.0003933712,0.00009125005],"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":[0.00006233258,0.00002468351,0.0009103334,0.0006061909,0.00017995,0.000003887157,0.0001057013,0.9200302,0.0463713,0.02795243,0.00003575557,0.003717281],"study_design_scores_gemma":[0.0008920741,0.000116519,0.00008252205,0.0005925871,0.00008240732,0.00000549488,0.0004755452,0.9343302,0.0547353,0.001269791,0.007128828,0.0002887846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9229575,0.0002621298,0.07290599,0.00001640708,0.0007733052,0.0002772705,0.00007522746,0.000402157,0.002330004],"genre_scores_gemma":[0.9979317,0.00001892894,0.001077838,0.000005069181,0.00008970175,0.00005834773,0.00009185636,0.0000565977,0.0006699506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07497419,"threshold_uncertainty_score":0.9999874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02892663657096204,"score_gpt":0.2729040243827179,"score_spread":0.2439773878117559,"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."}}