{"id":"W4221032662","doi":"10.3390/w14071122","title":"Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale","year":2022,"lang":"en","type":"article","venue":"Water","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canmore Museum and Geoscience Centre; University of Saskatchewan","funders":"Peking University; Ministry of Science and Technology, Taiwan","keywords":"Environmental science; Precipitation; Snow; Global Precipitation Measurement; Climatology; Latitude; Meteorology; Scale (ratio); Geology; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003325339,0.0007657905,0.0004092414,0.001079548,0.0002832121,0.000729462,0.0005314466,0.0004627228,0.0008550374],"category_scores_gemma":[0.003130278,0.000168467,0.0004931801,0.001045097,0.0001594498,0.001310527,0.0005126489,0.000300064,0.0002953809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004683908,"about_ca_system_score_gemma":0.0004545084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01142073,"about_ca_topic_score_gemma":0.01486965,"domain_scores_codex":[0.9992437,0.0002530454,0.00007107558,0.0001686351,0.0001823916,0.00008117589],"domain_scores_gemma":[0.9987828,0.0003424204,0.0001743222,0.0002681674,0.0003769356,0.0000553806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001794362,0.0005354123,0.3853076,0.0004085254,0.0009517084,0.0001688987,0.0003631352,0.3500425,0.01870329,0.002581844,0.004730092,0.2344126],"study_design_scores_gemma":[0.0001297109,0.00039282,0.4397138,0.00005227834,0.0001993679,0.0001044441,0.0003367523,0.5337319,0.01816662,0.0006161769,0.006480703,0.00007542627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9733373,0.0004191322,0.01579625,0.0001162606,0.00003546978,0.00008187507,0.005117117,0.0007341128,0.004362423],"genre_scores_gemma":[0.9591994,0.0001078776,0.02974167,0.0000562301,0.00001993913,0.00004960292,0.01019293,0.00007484412,0.0005575449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01142073,"threshold_uncertainty_score":0.02270848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05042126256578285,"score_gpt":0.2779574090178998,"score_spread":0.2275361464521169,"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."}}