{"id":"W3165736499","doi":"10.1371/journal.pone.0252133","title":"Future changes in the intensity and frequency of precipitation extremes over China in a warmer world: Insight from a large ensemble","year":2021,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Climate variability and models","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Precipitation; Environmental science; Climatology; Quantile; Global warming; Climate change; Extreme value theory; Return period; China; Intensity (physics); Climate model; Atmospheric sciences; Meteorology; Statistics; Geography; Mathematics; Ecology; Geology; Biology; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005943519,0.0003056629,0.0003582125,0.0002872772,0.0004379345,0.0004575946,0.0004138239,0.0003975705,0.0005385176],"category_scores_gemma":[0.001034498,0.0001732348,0.0007145876,0.0004351562,0.0002581604,0.0006779744,0.0003157552,0.0003970002,0.00005009316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006625503,"about_ca_system_score_gemma":0.0007525083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06448506,"about_ca_topic_score_gemma":0.05149224,"domain_scores_codex":[0.9999117,0.00001928313,0.000004839354,0.00002959351,0.00001488954,0.00001971125],"domain_scores_gemma":[0.9997086,0.00009302981,0.00004229965,0.00004908815,0.00006445855,0.00004248781],"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":[0.00005379943,0.00004261876,0.1531096,0.00001895193,0.000207188,0.0001622766,0.0000739975,0.8365481,0.002299008,0.0007061205,0.000493754,0.006284599],"study_design_scores_gemma":[0.00001277769,0.00001953326,0.0617453,0.000003384483,0.00006187006,0.00001995641,0.00004816598,0.9367663,0.0004274677,0.000553011,0.0003253032,0.00001699469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963458,0.00004259946,0.002796685,0.00007459039,0.00000681282,0.000004776301,0.0002807254,0.00002970429,0.0004182782],"genre_scores_gemma":[0.998111,0.00005446928,0.001098554,0.00002003704,0.000006195812,0.000009582388,0.0005596815,0.000007061467,0.0001333679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06448506,"threshold_uncertainty_score":0.1282195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03134290619965412,"score_gpt":0.2245546613976503,"score_spread":0.1932117551979962,"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."}}