{"id":"W3128150297","doi":"10.1029/2020wr028300","title":"How Do Climate and Catchment Attributes Influence Flood Generating Processes? A Large‐Sample Study for 671 Catchments Across the Contiguous USA","year":2021,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":175,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Engineering and Physical Sciences Research Council","keywords":"Flood myth; Hydrometeorology; Environmental science; Snowmelt; Climate change; Precipitation; 100-year flood; Drainage basin; Hydrology (agriculture); Flood forecasting; Flash flood; Snow; Climatology; Meteorology; Geography; Geology; Cartography","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.002567471,0.0002005229,0.0002355819,0.00003318969,0.002596889,0.0006365275,0.0004535831,0.00005943308,0.00006300224],"category_scores_gemma":[0.0003433592,0.0001169131,0.00003774549,0.0002818024,0.0004573484,0.0002422945,0.002692155,0.000261872,0.00005564088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000680259,"about_ca_system_score_gemma":0.000007489239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007001015,"about_ca_topic_score_gemma":0.002647009,"domain_scores_codex":[0.9967337,0.00036902,0.0002296207,0.0007046204,0.0006609628,0.001302041],"domain_scores_gemma":[0.9990361,0.0002978054,0.00004534731,0.0004156615,0.0001037214,0.000101375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008522079,0.0003728229,0.9341393,0.0001715849,0.000139533,0.00005373855,0.05980778,0.000753822,0.00325331,0.00000746865,0.0005480004,0.0006674772],"study_design_scores_gemma":[0.008445307,0.002206139,0.3220742,0.0001552056,0.0001941534,0.00003544788,0.1065715,0.001973742,0.07212612,0.001346147,0.4834608,0.001411282],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941226,0.000355476,0.000108224,0.003964063,0.00003635869,0.001248518,0.00006194953,0.00002353521,0.00007928415],"genre_scores_gemma":[0.9969491,0.0001290806,0.0001901316,0.0002301747,0.00005819345,0.0007453971,0.00002171465,0.00001749766,0.001658689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.612065,"threshold_uncertainty_score":0.9987016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04287769086286694,"score_gpt":0.3364138251106404,"score_spread":0.2935361342477735,"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."}}