{"id":"W2619612306","doi":"10.5194/hess-2017-252","title":"On the Relationship Between Flood and Contributing Area","year":2017,"lang":"en","type":"article","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Environment and Climate Change Canada","funders":"Environment and Climate Change Canada","keywords":"Flood myth; Streamflow; Hydrology (agriculture); Environmental science; Drainage basin; Watershed; Surface runoff; 100-year flood; Power function; Magnitude (astronomy); Watershed area; Power law; Geology; Statistics; Geography; Mathematics; Physics; Cartography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0008176744,0.0001285854,0.00007254555,0.0003801878,0.0001343398,0.000515905,0.0002274665,0.0001749542,0.001249524],"category_scores_gemma":[0.005787228,0.0001035497,0.0001217339,0.0004048798,0.0003953495,0.0002821452,0.0001867054,0.0001949899,0.000158714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009973039,"about_ca_system_score_gemma":0.0008132139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08360424,"about_ca_topic_score_gemma":0.06504623,"domain_scores_codex":[0.9998167,0.00006760538,0.000006436708,0.00003563538,0.00004945285,0.0000241536],"domain_scores_gemma":[0.9969207,0.002182498,0.0002110243,0.00009618841,0.0004776341,0.0001119745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007418656,0.00001899925,0.9370213,0.00001676504,0.00005898536,0.0001042177,0.0001269057,0.05008483,0.001678335,0.001550276,0.000306948,0.008958269],"study_design_scores_gemma":[0.000007050814,0.00005101921,0.8080937,0.00001127995,0.00003270144,0.0001566967,0.000233682,0.1871182,0.001036486,0.002409739,0.0008368411,0.00001254012],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946674,0.00005789164,0.003463768,0.00006666985,0.00000213266,0.000007718626,0.0001700707,0.0000170101,0.001547438],"genre_scores_gemma":[0.9992798,0.0000282158,0.0003942327,0.000005882559,0.000001144714,0.000001977117,0.00006767825,0.000003207089,0.0002177695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08360424,"threshold_uncertainty_score":0.1662352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05056235652389782,"score_gpt":0.2594484427151718,"score_spread":0.2088860861912739,"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."}}