{"id":"W3164545656","doi":"10.1029/2020wr029466","title":"Advancing Space‐Time Simulation of Random Fields: From Storms to Cyclones and Beyond","year":2021,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Advection; Storm; Copula (linguistics); Positive definiteness; Gaussian; Statistical physics; Random field; Meteorology; Computer science; Anisotropy; Environmental science; Mathematics; Physics; Econometrics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006618317,0.00006909076,0.0001714065,0.00007257792,0.0001608909,0.00002807127,0.0001272039,0.00007701702,0.004279155],"category_scores_gemma":[0.0001479847,0.00004841081,0.00003807752,0.0002314392,0.0001507542,0.0001029508,0.0004024613,0.0001522369,0.0004269676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002824825,"about_ca_system_score_gemma":0.000003288225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000994451,"about_ca_topic_score_gemma":0.0006071294,"domain_scores_codex":[0.9986219,0.000250068,0.0001478173,0.0002876529,0.000396298,0.0002963122],"domain_scores_gemma":[0.999301,0.000319047,0.00001590489,0.0002316796,0.00002337414,0.0001090254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007102462,0.0001336851,0.1397323,0.00002248771,0.0001146131,0.0001416237,0.03752711,0.3955513,0.4157811,0.000004727668,0.001325633,0.008955123],"study_design_scores_gemma":[0.003513322,0.0004694756,0.04472689,0.00006502507,0.00009710754,0.00001053439,0.002486543,0.2206031,0.5266247,0.009663753,0.1910706,0.0006689029],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933093,0.0001111848,0.0005241079,0.001601184,0.0000118261,0.00009207493,0.000004165834,0.000008877765,0.004337272],"genre_scores_gemma":[0.9958765,0.00001409177,0.0004313295,0.00009294348,0.00003756098,0.000005918329,0.00001249394,0.000006763256,0.003522432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.189745,"threshold_uncertainty_score":0.9966311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0126442619599403,"score_gpt":0.288767137565092,"score_spread":0.2761228756051518,"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."}}