{"id":"W2674211945","doi":"10.1038/s41598-017-04282-8","title":"Global rainfall erosivity assessment based on high-temporal resolution rainfall records","year":2017,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":644,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Oceanic and Atmospheric Administration; Ministry of Earth Sciences; Lomonosov Moscow State University; Korea Meteorological Administration; Universidad de Costa Rica; Centro Nacional de Investigaciones de Café","keywords":"Environmental science; Precipitation; Erosion; Climatology; Temperate climate; Climate change; Arid; Physical geography; Hydrology (agriculture); Geography; Geology; Meteorology","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":[0.0009128921,0.0003856577,0.0003164499,0.001870222,0.0001093744,0.0005084262,0.000223622,0.0003137038,0.0004111573],"category_scores_gemma":[0.001102325,0.0001287284,0.0004171712,0.001900545,0.0001856062,0.0005575922,0.0005665441,0.000205702,0.0001289465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000211315,"about_ca_system_score_gemma":0.0001840213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00695636,"about_ca_topic_score_gemma":0.007011135,"domain_scores_codex":[0.9997863,0.00005531425,0.00002621964,0.00005968891,0.00003833747,0.00003413104],"domain_scores_gemma":[0.9993539,0.0001509496,0.000187219,0.0001074284,0.0001473261,0.00005306981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003066783,0.0001693496,0.8569552,0.000122604,0.000387689,0.0003566072,0.0002261815,0.08462223,0.01527883,0.0002745448,0.000729009,0.04057119],"study_design_scores_gemma":[0.00002064782,0.00009478081,0.9384561,0.00001680038,0.00007428385,0.00007919747,0.0002372375,0.05827123,0.00203842,0.0001264104,0.00056204,0.0000228962],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99546,0.00005655646,0.002122496,0.00001817153,0.000002673428,0.00001738856,0.001772494,0.00007169228,0.0004785049],"genre_scores_gemma":[0.9956316,0.00004153177,0.002233532,0.00000412682,0.000003194554,0.00001116188,0.002008526,0.000005590098,0.00006071436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00695636,"threshold_uncertainty_score":0.01383173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02645840764776945,"score_gpt":0.2691313496638117,"score_spread":0.2426729420160423,"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."}}