{"id":"W4386986716","doi":"10.3850/978-981-18-8071-1_p546-cd","title":"Return Periods of Extreme Events in the Changing Climate: LEYP Model","year":2023,"lang":"en","type":"article","venue":"","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Return period; Climate change; Extreme weather; Environmental science; Reliability (semiconductor); Econometrics; Computer science; Extreme value theory; Pace; Climate model; Stochastic process; Poisson distribution; Climatology; Mathematics; Statistics; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006095887,0.0003108549,0.0006250047,0.0003888979,0.0003470501,0.001278578,0.001547673,0.001305566,0.004131017],"category_scores_gemma":[0.002569597,0.0002615681,0.000647096,0.000755447,0.0004051014,0.0009060511,0.0006784445,0.001385909,0.0004846795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007610726,"about_ca_system_score_gemma":0.0007978114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0179807,"about_ca_topic_score_gemma":0.008290105,"domain_scores_codex":[0.9998517,0.00004665821,0.000005757376,0.00004103539,0.00002289596,0.00003194964],"domain_scores_gemma":[0.9993907,0.0003005387,0.000107402,0.00004645537,0.00007539854,0.00007940209],"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":[0.00004477244,0.00001265876,0.002051728,0.00001844809,0.00002528857,0.00007448945,0.00002003839,0.9852904,0.0002709653,0.008372671,0.00153049,0.002288029],"study_design_scores_gemma":[0.000006684985,0.000008511403,0.0007204755,0.000003521107,0.00001036994,0.00001572228,0.00001282518,0.9950466,0.00007493125,0.00366131,0.0004316046,0.000007549032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8012562,0.0006518743,0.1494124,0.005109703,0.0002905084,0.0000558975,0.0058268,0.0009180293,0.03647859],"genre_scores_gemma":[0.9879665,0.0002916466,0.003046214,0.0001059205,0.00006465908,0.00003320729,0.0008879122,0.0001126833,0.007491249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0179807,"threshold_uncertainty_score":0.03575206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2190860906884158,"score_gpt":0.3598337521318646,"score_spread":0.1407476614434489,"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."}}