{"id":"W4412879807","doi":"10.1080/19401493.2025.2540927","title":"Adapting building performance simulation for climate resilience: accounting for urban microclimates and future climates","year":2025,"lang":"en","type":"article","venue":"Journal of Building Performance Simulation","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Université de Sherbrooke","funders":"","keywords":"Microclimate; Resilience (materials science); Environmental science; Environmental resource management; Climate change; Architectural engineering; Urban resilience; Geography; Environmental planning; Engineering; Civil engineering; Urban planning; Ecology","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":[0.0009737388,0.0002574555,0.0003458764,0.0004536828,0.0005917377,0.0001702637,0.0001785665,0.0001881071,0.000002577553],"category_scores_gemma":[0.0001006148,0.0002540108,0.0001169151,0.0003667164,0.00003069632,0.00146004,0.00003923159,0.0002203183,1.158418e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001441479,"about_ca_system_score_gemma":0.00003425339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.712475e-7,"about_ca_topic_score_gemma":3.792867e-7,"domain_scores_codex":[0.9983084,0.00001478107,0.000843966,0.0002112078,0.0001920254,0.0004296516],"domain_scores_gemma":[0.9984837,0.000496228,0.0004421922,0.0001387681,0.0003889599,0.00005020234],"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":[0.0002681402,0.00001172741,0.01498823,0.0009793432,0.0000425891,1.291903e-7,0.0001549675,0.9529178,0.005655811,0.0003549042,0.00003724384,0.02458915],"study_design_scores_gemma":[0.001294271,0.0001243181,0.003177395,0.000641358,0.00009313097,0.00000498473,0.00009074654,0.9818131,0.009389829,0.000102423,0.003019975,0.0002485138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7821388,0.0007805479,0.2158242,0.00004762304,0.000766289,0.0003016726,0.000005404006,0.00009671156,0.00003869179],"genre_scores_gemma":[0.9469101,0.0009338617,0.05128286,0.00004710178,0.0007369122,0.00002151114,0.00001276334,0.00004414636,0.00001076797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1647713,"threshold_uncertainty_score":0.9999912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007123918521105777,"score_gpt":0.2565846471534698,"score_spread":0.2494607286323641,"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."}}