{"id":"W3005580059","doi":"10.1016/j.scitotenv.2020.137350","title":"Evaluating the added values of regional climate modeling over China at different resolutions","year":2020,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Climate variability and models","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Prince Edward Island; University of Regina","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China","keywords":"Downscaling; Climate model; Environmental science; Precipitation; Climatology; Common spatial pattern; Transient climate simulation; Spatial ecology; Climate change; Meteorology; Computer science; Geography; Geology; Mathematics; Statistics","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":[0.003160315,0.001361261,0.0005572607,0.00100499,0.0007522391,0.001594685,0.001206173,0.001563331,0.001747959],"category_scores_gemma":[0.01181613,0.0005999217,0.00104324,0.001576696,0.0006683216,0.002488173,0.000734847,0.001149689,0.0001600189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002353831,"about_ca_system_score_gemma":0.001243042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0349443,"about_ca_topic_score_gemma":0.03966963,"domain_scores_codex":[0.9990534,0.0004765684,0.00005636936,0.0001406372,0.0001724394,0.0001005448],"domain_scores_gemma":[0.9913469,0.006514379,0.0003591747,0.0005922941,0.0009310607,0.000256299],"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":[0.000531605,0.0001491296,0.01181256,0.00005888466,0.0001754884,0.0001251829,0.00003557848,0.9733165,0.001306379,0.001047549,0.0004679461,0.01097326],"study_design_scores_gemma":[0.00008957798,0.0001096385,0.007720773,0.00001466727,0.0001691339,0.0000190245,0.00007080952,0.9879579,0.00265723,0.0008588291,0.0003108404,0.00002157242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889271,0.0004051059,0.003708055,0.0005800358,0.00009811898,0.00003133147,0.0009152977,0.0002089145,0.005126121],"genre_scores_gemma":[0.9961028,0.00009228077,0.002988453,0.00003814315,0.00002503966,0.00001425152,0.0003930843,0.00003751364,0.0003085147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0349443,"threshold_uncertainty_score":0.06948179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07143870336825427,"score_gpt":0.2872783502601073,"score_spread":0.215839646891853,"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."}}