{"id":"W2173090123","doi":"10.3390/atmos6111833","title":"An Assessment of the South Asian Summer Monsoon Variability for Present and Future Climatologies Using a High Resolution Regional Climate Model (RegCM4.3) under the AR5 Scenarios","year":2015,"lang":"en","type":"article","venue":"Atmosphere","topic":"Climate variability and models","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Tsinghua National Laboratory for Information Science and Technology; University of East Anglia; Abdus Salam International Centre for Theoretical Physics; International Development Research Centre","keywords":"Climatology; Environmental science; Precipitation; Climate model; Monsoon; Anticyclone; Climate change; Representative Concentration Pathways; Downscaling; Tropical monsoon climate; East Asian Monsoon; Atmospheric sciences; Geology; Meteorology; Geography; Oceanography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001244292,0.0001809502,0.0002120371,0.000002028388,0.0003552125,0.00004317403,0.0003401191,0.0001544766,0.00003926038],"category_scores_gemma":[0.00002696355,0.0001068674,0.00009106081,0.000127159,0.0004796642,0.000265191,0.0003565678,0.000170646,0.000001072858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002284549,"about_ca_system_score_gemma":0.0000847322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005336526,"about_ca_topic_score_gemma":0.0002161832,"domain_scores_codex":[0.998242,0.0002888939,0.000312348,0.0004354786,0.0003716655,0.0003496079],"domain_scores_gemma":[0.998816,0.0001123218,0.0001953208,0.0007346568,0.00004104175,0.0001007123],"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":[0.0001454453,0.0002257367,0.07014977,0.00004719159,0.00002162789,2.308729e-7,0.001706642,0.913078,0.0003707704,0.01349253,0.0003785327,0.0003834972],"study_design_scores_gemma":[0.0004659734,0.00006853719,0.04825419,0.00001569878,0.00006868788,0.000004545047,0.004300676,0.9241383,0.00002365227,0.02228151,0.000237212,0.0001410203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783932,0.00003935357,0.01610871,0.003773651,0.0001209421,0.00083595,0.00006933742,0.00003144766,0.0006273939],"genre_scores_gemma":[0.9736806,0.00002329584,0.02596287,0.0001843207,0.00006851173,0.00004035157,0.00001041463,0.00001576275,0.00001393416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02189558,"threshold_uncertainty_score":0.4357928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06224258245528719,"score_gpt":0.3149343985297959,"score_spread":0.2526918160745087,"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."}}