{"id":"W4323360269","doi":"10.1029/2022wr034094","title":"Large‐Domain Multisite Precipitation Generation: Operational Blueprint and Demonstration for 1,000 Sites","year":2023,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Marginal distribution; Advection; Precipitation; Gaussian; Stochastic simulation; Process (computing); Domain (mathematical analysis); Algorithm; Statistical physics; Meteorology; Mathematics; Random variable; Statistics; Geography; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001141086,0.0004781038,0.0004117254,0.0003760397,0.0003534506,0.0004099483,0.00125391,0.0007260822,0.003498692],"category_scores_gemma":[0.002185472,0.0002404672,0.0003515758,0.0007116772,0.000410818,0.0005265932,0.0005723679,0.000725781,0.0004236612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004634813,"about_ca_system_score_gemma":0.0006261446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01753516,"about_ca_topic_score_gemma":0.0118111,"domain_scores_codex":[0.9997703,0.00009447335,0.00001290591,0.00003647201,0.00005571574,0.00003023094],"domain_scores_gemma":[0.9987379,0.0005975859,0.00005676028,0.0002777748,0.0002136596,0.0001163175],"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":[0.0003544258,0.0003866289,0.01027032,0.00006380184,0.00004915829,0.0002648531,0.00009218982,0.953074,0.002487953,0.003340398,0.004827422,0.02478888],"study_design_scores_gemma":[0.00006031042,0.00002608891,0.0008211401,0.000002319556,0.000002858937,0.00001039917,0.00001400764,0.9971885,0.0008697598,0.0006741493,0.0003256215,0.000004852768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8578995,0.0001292547,0.1200586,0.0007095647,0.000139337,0.0002237214,0.002880762,0.00901024,0.008949079],"genre_scores_gemma":[0.9545743,0.00003183184,0.04324844,0.00004283863,0.000008161631,0.00007083057,0.00136041,0.0001291082,0.0005340771],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01753516,"threshold_uncertainty_score":0.03486615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05811950732493012,"score_gpt":0.3261220832738248,"score_spread":0.2680025759488947,"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."}}