{"id":"W2080186500","doi":"10.1002/asl.267","title":"Summary of recommendations of the first workshop on Postprocessing and Downscaling Atmospheric Forecasts for Hydrologic Applications held at Météo‐France, Toulouse, France, 15–18 June 2009","year":2010,"lang":"en","type":"article","venue":"Atmospheric Science Letters","topic":"Climate variability and models","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Hydro (Canada)","funders":"","keywords":"Downscaling; Climatology; Environmental science; Meteorology; Range (aeronautics); Hydrological modelling; Structural basin; Geography; Geology; Engineering; Precipitation","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":[0.0006433884,0.0001885526,0.0002310206,0.000004594744,0.0008158702,0.0000406869,0.0007088189,0.00009271034,0.0001768587],"category_scores_gemma":[0.0001343125,0.000143638,0.0000930528,0.001384431,0.001786336,0.0003534726,0.0003203474,0.0002084934,0.000007812582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007262383,"about_ca_system_score_gemma":0.00002372852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001325908,"about_ca_topic_score_gemma":0.0002019228,"domain_scores_codex":[0.9981906,0.00002190343,0.0003980958,0.0005864428,0.000374083,0.0004288577],"domain_scores_gemma":[0.9985799,0.0003763243,0.0003168458,0.0006005224,0.00003037698,0.00009606055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001401193,0.000686442,0.2703194,0.0002250233,0.0000320888,8.936635e-7,0.002067677,0.1256872,0.5027744,0.0005368971,0.01266178,0.08486798],"study_design_scores_gemma":[0.002974686,0.0004380966,0.1697489,0.0005475547,0.0001948899,0.00004332268,0.000542743,0.5776893,0.0235744,0.004285038,0.2181356,0.0018255],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820262,0.00004979071,0.006234883,0.009494378,0.0003485626,0.0008309673,0.00002027421,0.00003017533,0.0009648314],"genre_scores_gemma":[0.9494894,0.00006041468,0.04521987,0.004460753,0.00004565978,0.0002106289,0.000004020127,0.00001936151,0.0004899096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4792,"threshold_uncertainty_score":0.6581831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01159351252395924,"score_gpt":0.2429911008650056,"score_spread":0.2313975883410463,"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."}}