{"id":"W4280500806","doi":"10.1371/journal.pclm.0000029","title":"Global hydro-climatological indicators and changes in the global hydrological cycle and rainfall patterns","year":2022,"lang":"en","type":"article","venue":"PLOS Climate","topic":"Climate variability and models","field":"Environmental Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Norsk Institutt for Vannforskning","keywords":"Precipitation; Water cycle; Environmental science; Climatology; Global change; Trend analysis; Global warming; Climate change; Meteorology; Geology; Geography; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007421597,0.0001721912,0.000222849,0.00002110402,0.0003549759,0.00005128457,0.0003333414,0.00008070315,0.001087709],"category_scores_gemma":[0.00004701683,0.0001226663,0.0000328522,0.0003173558,0.0002999243,0.00008470077,0.00137679,0.000201226,0.00002032709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001714706,"about_ca_system_score_gemma":0.000003444603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002212808,"about_ca_topic_score_gemma":0.0007389105,"domain_scores_codex":[0.9980989,0.0003240697,0.0002121323,0.0004967916,0.0003649516,0.0005031901],"domain_scores_gemma":[0.9994594,0.00013046,0.00007073454,0.000231684,0.000001314775,0.0001063717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004443138,0.0002687871,0.9955606,0.0000138137,0.000005305162,0.0000503976,0.0005215304,0.0002522302,0.00003690543,0.002696465,0.00002103221,0.0005284265],"study_design_scores_gemma":[0.0006424186,0.0002907973,0.9725012,0.000006565119,0.00002930422,0.0001833958,0.0007458374,0.009220065,0.000004980733,0.01521857,0.0009036844,0.0002531464],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902772,0.00005176927,0.0000040919,0.003460043,0.00003350873,0.0003353322,0.0002913685,0.00005077595,0.005495874],"genre_scores_gemma":[0.9973959,0.000205581,0.00008572148,0.002153044,0.00001162374,0.0001224852,0.00001924936,0.000005040851,0.000001376457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02305944,"threshold_uncertainty_score":0.9998254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01779611213502815,"score_gpt":0.2399093645976607,"score_spread":0.2221132524626326,"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."}}