{"id":"W4386412514","doi":"10.1007/978-981-19-9822-5_281","title":"Assessing the Thermal Resilience of Buildings Using Multiple Outage Events","year":2023,"lang":"en","type":"book-chapter","venue":"Environmental science and engineering","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Resilience (materials science); Storm; Upgrade; Environmental science; Psychological resilience; Computer science; Climate change; Event (particle physics); Meteorology; Reliability engineering; Climatology; Engineering; Geography; Geology","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":[],"consensus_categories":[],"category_scores_codex":[0.0005457452,0.0002580765,0.0002117854,0.00006539743,0.0004315395,0.00005124754,0.0004283085,0.00007528999,0.000126046],"category_scores_gemma":[0.00004463314,0.0001930852,0.00006154861,0.0001077825,0.001053138,0.0004830013,0.0009089223,0.0002217993,0.00005563322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002160943,"about_ca_system_score_gemma":0.00001151499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004136969,"about_ca_topic_score_gemma":0.00000249765,"domain_scores_codex":[0.9981214,0.000005188711,0.0002396189,0.0004613851,0.0008024649,0.0003699062],"domain_scores_gemma":[0.999463,0.0000781964,0.0001197768,0.000244796,0.000002307759,0.0000919354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000004866226,0.00003334685,0.04486913,0.00005621238,0.00004317163,0.00002559672,0.001198318,0.05829629,0.870317,0.0003928101,0.00008430043,0.02467898],"study_design_scores_gemma":[0.0007148228,0.0001669803,0.8768317,0.0009663419,0.0001848449,0.00005958023,0.00112535,0.08163861,0.01330385,0.0004826077,0.02230013,0.002225158],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981959,0.0001538828,0.0001270671,0.00005346927,0.000278577,0.0002331416,0.00001425629,0.00004589601,0.01713475],"genre_scores_gemma":[0.9912739,0.0001109366,0.000536764,0.00002710136,0.00005919234,0.00000398734,0.000001281972,0.00003547721,0.007951378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8570131,"threshold_uncertainty_score":0.7873785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01444222458250174,"score_gpt":0.2168211636436246,"score_spread":0.2023789390611229,"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."}}