{"id":"W2588503365","doi":"10.1002/2016gl072201","title":"Time‐varying extreme rainfall intensity‐duration‐frequency curves in a changing climate","year":2017,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":177,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Precipitation; Environmental science; Climate change; Duration (music); Probabilistic logic; Markov chain; Climatology; Intensity (physics); Reliability (semiconductor); Markov chain Monte Carlo; Bayesian probability; Computer science; Meteorology; Econometrics; Statistics; Mathematics; Geology; Geography; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008160547,0.0001489041,0.0001363899,0.000523355,0.0001557118,0.0003880243,0.0003003757,0.0003650773,0.0007380898],"category_scores_gemma":[0.003512698,0.0001329144,0.0002127693,0.0005079231,0.0003275665,0.0005178299,0.0002522442,0.0003740455,0.00008179287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003757525,"about_ca_system_score_gemma":0.0001629729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006364767,"about_ca_topic_score_gemma":0.004104156,"domain_scores_codex":[0.9998424,0.00005694327,0.000009450452,0.00003369414,0.00002993694,0.00002763193],"domain_scores_gemma":[0.9980215,0.001204245,0.0003498855,0.0001415424,0.0001949294,0.00008798129],"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":[0.0001903922,0.00006387261,0.1636568,0.00004472255,0.00008806624,0.0003126385,0.0002172793,0.812465,0.006440088,0.004329992,0.0005944825,0.01159665],"study_design_scores_gemma":[0.00001098008,0.00005739898,0.1660452,0.000006989693,0.00002009114,0.0001085273,0.0001473502,0.8286117,0.001430095,0.003051186,0.0004785857,0.00003186725],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895663,0.00002058773,0.009011855,0.00007580801,0.000004600108,0.000008041376,0.0002394637,0.00005865463,0.001014678],"genre_scores_gemma":[0.9992029,0.000009156576,0.0006227645,0.00000426375,0.000001907635,0.000002887103,0.00007910936,0.000005553924,0.00007152389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006364767,"threshold_uncertainty_score":0.01265544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04736813058221395,"score_gpt":0.3142758715262239,"score_spread":0.26690774094401,"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."}}