{"id":"W2104606748","doi":"10.1002/joc.4500","title":"Assessment of <scp>NARCCAP</scp> model in simulating rainfall extremes using a spatially constrained regionalization method","year":2015,"lang":"en","type":"article","venue":"International Journal of Climatology","topic":"Climate variability and models","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Climatology; GCM transcription factors; Climate model; Environmental science; General Circulation Model; Downscaling; Climate change; Meteorology; Geography; Precipitation; Geology","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":[0.002310808,0.0006157629,0.0004965743,0.0003908279,0.0004023262,0.000630762,0.001322217,0.0005922464,0.0008450296],"category_scores_gemma":[0.004522189,0.0004119107,0.0005726686,0.000540892,0.0003714986,0.0005954462,0.0006207893,0.0006337934,0.0001274789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00109331,"about_ca_system_score_gemma":0.001518967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1099072,"about_ca_topic_score_gemma":0.06009043,"domain_scores_codex":[0.9994094,0.0003347415,0.00003141465,0.0001079591,0.00007319983,0.00004331689],"domain_scores_gemma":[0.9978924,0.0009219974,0.0002427913,0.0003319567,0.0005301053,0.0000807694],"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":[0.00004688796,0.00003635113,0.00792555,0.00001146978,0.00005726476,0.00002364626,0.00001763077,0.9876516,0.0006548844,0.0004322111,0.0003134891,0.002828977],"study_design_scores_gemma":[0.00001748481,0.00001596401,0.001353202,0.000002180094,0.000008642164,0.000004153241,0.000009252963,0.9980078,0.0003643802,0.0000702095,0.0001418746,0.00000484391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9603524,0.000108251,0.0319583,0.0003778907,0.00003380515,0.000105994,0.00097108,0.001331516,0.004760751],"genre_scores_gemma":[0.9748015,0.00002960358,0.02419689,0.00006637129,0.000009253641,0.0000731093,0.0004655114,0.00008424078,0.0002733893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1099072,"threshold_uncertainty_score":0.2185349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08790169174638816,"score_gpt":0.3862990730976781,"score_spread":0.29839738135129,"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."}}