{"id":"W3035880473","doi":"10.5327/z2176-947820200624","title":"ANÁLISE DE PROJEÇÕES DAS MUDANÇAS CLIMÁTICAS SOBRE PRECIPITAÇÃO E TEMPERATURA NAS REGIÕES HIDROGRÁFICAS BRASILEIRAS PARA O SÉCULO XXI","year":2020,"lang":"pt","type":"article","venue":"Revista Brasileira de Ciências Ambientais","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Center of Mathematical Sciences and Applications, Harvard University; Irish Centre for High-End Computing; National Oceanic and Atmospheric Administration; Commonwealth Scientific and Industrial Research Organisation","keywords":"Environmental science; Downscaling; Climatology; Climate model; Geography; Climate change; Atmospheric sciences; Physics; Meteorology; Geology; Precipitation","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.001082612,0.002052589,0.001901644,0.00007750223,0.001308344,0.001198613,0.002453143,0.001128437,0.003817961],"category_scores_gemma":[0.0006181916,0.002130446,0.001122948,0.001988814,0.002034863,0.001397928,0.00178968,0.001983101,0.002497288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002222543,"about_ca_system_score_gemma":0.0003494658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006097457,"about_ca_topic_score_gemma":0.0000837535,"domain_scores_codex":[0.9885041,0.001034876,0.002094279,0.003167626,0.0019391,0.003260007],"domain_scores_gemma":[0.9938429,0.0003472869,0.001090826,0.001944178,0.00005841556,0.002716409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005686808,0.001321803,0.9328117,0.0008492564,0.0003878405,0.001097951,0.01120312,0.004600677,0.01597276,0.0006605777,0.02275448,0.007771149],"study_design_scores_gemma":[0.002872625,0.002012171,0.8826333,0.0009198608,0.001118366,0.00049976,0.0110619,0.02937207,0.001721733,0.00004663209,0.06369664,0.004044932],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841821,0.002680013,0.004559007,0.001771238,0.0003984608,0.002755887,0.0003172714,0.0005588508,0.002777139],"genre_scores_gemma":[0.9788254,0.001864199,0.007601425,0.006733079,0.0007794506,0.0002261763,0.0002016518,0.0004431044,0.0033255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0501784,"threshold_uncertainty_score":0.9999918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02809648474895383,"score_gpt":0.2780948637540205,"score_spread":0.2499983790050667,"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."}}