{"id":"W2981559229","doi":"10.1088/1757-899x/609/6/062022","title":"Building-to-vehicle-to-building approach for the NZEB target at a micro-grid level: a comprehensive sensitivity and parametric post-optimality analysis","year":2019,"lang":"en","type":"article","venue":"IOP Conference Series Materials Science and Engineering","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Renewable energy; Zero-energy building; Photovoltaic system; Grid; Roof; Electricity; Sensitivity (control systems); Automotive engineering; Parametric statistics; Computer science; Engineering; Civil engineering; Electrical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006925132,0.0003194994,0.0005097272,0.0004365253,0.0002869287,0.0005094816,0.0002769458,0.00008909834,0.00001689605],"category_scores_gemma":[0.0001417463,0.0002572672,0.00005302615,0.00165337,0.0001227406,0.0004507193,0.0002714993,0.0001280174,0.00000282218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001100353,"about_ca_system_score_gemma":0.00004473765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000843349,"about_ca_topic_score_gemma":0.00000592645,"domain_scores_codex":[0.998197,0.00002051615,0.0002877218,0.0005418918,0.0002905339,0.0006622936],"domain_scores_gemma":[0.9989282,0.0001605918,0.00004894929,0.0003242032,0.0003121168,0.0002259515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003080083,0.000002897348,0.0002670536,0.0001252639,0.00006454793,9.046903e-7,0.0002120599,0.2060706,0.7922043,0.0003560679,0.00001462737,0.0006509115],"study_design_scores_gemma":[0.0002028785,0.00013174,0.0568234,0.00003077649,0.00009237104,0.00003969173,0.0001617411,0.3878746,0.553478,0.00002112052,0.000663499,0.0004801403],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9341221,0.0001299679,0.06432687,0.0001660723,0.0003095352,0.0006254751,0.0001786266,0.0001284232,0.00001296955],"genre_scores_gemma":[0.9423477,0.000039659,0.0573366,0.0001140851,0.00007035802,0.00004470848,0.000007158695,0.00002619795,0.00001351549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2387263,"threshold_uncertainty_score":0.999988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01389632965997164,"score_gpt":0.2203043467677162,"score_spread":0.2064080171077446,"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."}}