{"id":"W2937348179","doi":"10.1002/hyp.13467","title":"On the relationship between flood and contributing area","year":2019,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Environment and Climate Change Canada","keywords":"Flood myth; Streamflow; Watershed; Power law; Exponent; Hydrology (agriculture); Environmental science; Return period; Drainage basin; Mathematics; Statistics; Geology; Geography; Cartography; Computer science","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":[0.001334144,0.000134796,0.00009815639,0.0005803386,0.0001489035,0.0006345892,0.0002550665,0.0003224224,0.001283529],"category_scores_gemma":[0.01743926,0.0001496843,0.0001627156,0.000484561,0.0003384236,0.0005929255,0.0002428917,0.0003243385,0.0001412484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005259068,"about_ca_system_score_gemma":0.0003687893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007703935,"about_ca_topic_score_gemma":0.004668339,"domain_scores_codex":[0.9997852,0.00009229901,0.00001060882,0.00004626635,0.0000407815,0.00002482125],"domain_scores_gemma":[0.9845822,0.01361522,0.0006260017,0.0002829989,0.000705288,0.0001882011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001502941,0.00005058922,0.6375895,0.00002553057,0.00006082122,0.0001274367,0.0001157489,0.3394585,0.002276009,0.005212654,0.0005126065,0.01442038],"study_design_scores_gemma":[0.00001217263,0.00006742774,0.2119983,0.00001332234,0.00002318854,0.0001493062,0.0001058784,0.7803382,0.001338667,0.00533696,0.000592556,0.00002394985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888638,0.00005875833,0.00848215,0.0001015042,0.00000481881,0.000009517079,0.000198158,0.00004013544,0.002241071],"genre_scores_gemma":[0.9990554,0.00001805858,0.000696274,0.000006007579,0.000002100511,0.00000329008,0.00006708836,0.000006243345,0.0001454521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007703935,"threshold_uncertainty_score":0.01531816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0366317979547563,"score_gpt":0.2372440092935129,"score_spread":0.2006122113387566,"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."}}