{"id":"W2106381703","doi":"10.1175/jhm-d-15-0025.1","title":"On the Remapping Procedure of Daily Precipitation Statistics and Indices Used in Regional Climate Model Evaluation","year":2015,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Environment and Climate Change Canada","funders":"","keywords":"Downscaling; Precipitation; Benchmark (surveying); Grid; Climate model; Climatology; Climate change; Environmental science; Index (typography); Computer science; Meteorology; Field (mathematics); Monsoon; Satellite; Geography; Mathematics; Geology; Cartography; Geodesy","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":[],"consensus_categories":[],"category_scores_codex":[0.003359959,0.00006378249,0.0001622222,0.00009245238,0.00003057172,0.000007569281,0.0001075458,0.0000619429,0.00005016017],"category_scores_gemma":[0.0006422481,0.00004387664,0.00001898401,0.0001201744,0.0001391786,0.0001766116,0.00004414611,0.0001494255,0.000002716561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001003146,"about_ca_system_score_gemma":0.00005387088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001948548,"about_ca_topic_score_gemma":0.0001136259,"domain_scores_codex":[0.9987677,0.0002280419,0.0003791333,0.0001040945,0.0004032034,0.0001178038],"domain_scores_gemma":[0.9990689,0.0003383516,0.0004144848,0.0000848547,0.00004694144,0.00004648441],"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":[0.0006228721,0.0002406655,0.04771143,0.00003670843,0.00002509013,0.000004144323,0.00938453,0.9271529,0.00853057,0.004093417,0.0009419377,0.001255786],"study_design_scores_gemma":[0.0009241176,0.0005902012,0.03742182,0.00003249812,0.00003682759,0.00004023427,0.0003132913,0.82432,0.00006993362,0.1361725,0.00001918238,0.00005940974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974392,0.00003742583,0.001083909,0.0009546407,0.00004531473,0.0001558247,0.00000733058,0.000001535143,0.0002748258],"genre_scores_gemma":[0.996876,0.00004601024,0.002902776,0.000150912,0.000008727608,0.000004496717,0.00000285881,0.000004103003,0.000004104583],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1320791,"threshold_uncertainty_score":0.1789238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06560530173410019,"score_gpt":0.2995175854805497,"score_spread":0.2339122837464496,"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."}}