{"id":"W7105694866","doi":"10.15480/882.16135","title":"Generative adversarial networks for downscaling hourly precipitation in the canadian prairies","year":2025,"lang":"en","type":"article","venue":"TUHH Open Research","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Downscaling; Climate model; Precipitation; Benchmark (surveying); Climate change; Key (lock); Fidelity; Coupled model intercomparison project; Spatial ecology; Adversarial system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00517498,0.00005976517,0.00008907977,0.00006859466,0.0007021533,0.0003769971,0.0007024014,0.00007483618,0.0001960058],"category_scores_gemma":[0.0004311948,0.0000448783,0.0000219084,0.0004895171,0.0002168527,0.0002616123,0.0002684425,0.0002578242,0.00002804098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004725769,"about_ca_system_score_gemma":0.0002218292,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5131809,"about_ca_topic_score_gemma":0.9262053,"domain_scores_codex":[0.9985019,0.00044345,0.0001424784,0.0002602137,0.0002503854,0.0004015924],"domain_scores_gemma":[0.9989359,0.0007274983,0.00001508799,0.000229577,0.00003292491,0.00005903516],"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":[0.001036002,0.0003994236,0.08598324,0.0000584302,0.00005557478,0.0000133585,0.03116185,0.4551795,0.0007456637,0.1895047,0.1983558,0.0375064],"study_design_scores_gemma":[0.002942961,0.0003908471,0.1542113,0.0001139789,0.00002129119,0.000001641182,0.005450415,0.5670061,0.0003457122,0.1218356,0.1472472,0.0004330075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5770592,0.00007092468,0.01030262,0.06854005,0.0004501057,0.01053809,0.0001017421,0.00001984121,0.3329174],"genre_scores_gemma":[0.9964998,0.000007022149,0.001159021,0.000445701,0.00004348867,0.0004831393,0.00003519358,0.00000438805,0.001322187],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4194407,"threshold_uncertainty_score":0.5400467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1279082809294181,"score_gpt":0.4165020518001873,"score_spread":0.2885937708707692,"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."}}