{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003586066,0.00009396668,0.0001137442,0.00001071686,0.0003163562,0.00001703467,0.000134161,0.00006407057,0.0006913235],"category_scores_gemma":[0.0009710123,0.00004978533,0.00001492872,0.0001246431,0.0002291688,0.00007376905,0.0002281151,0.0001568549,0.0008554158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001063877,"about_ca_system_score_gemma":0.000001497704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005576487,"about_ca_topic_score_gemma":0.000004448819,"domain_scores_codex":[0.9992607,0.00005478545,0.0001024248,0.0002379231,0.0001137966,0.000230416],"domain_scores_gemma":[0.998086,0.001729978,0.00004255417,0.000108615,0.000003614026,0.00002919049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001239393,0.00001503554,0.9967086,0.00000946873,0.000008415626,0.000001480353,0.00007292459,0.0002764543,0.000009554533,0.002414447,0.0004158378,0.00005542892],"study_design_scores_gemma":[0.0002176635,0.0001842111,0.9242639,0.000009221442,0.00001897699,0.000001155208,0.00003199231,0.0001449277,0.00008460371,0.07329012,0.001648645,0.0001046048],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693878,0.00004375745,0.00008336581,0.005782212,0.00001866967,0.0002014742,0.000001738396,0.00004610993,0.02443491],"genre_scores_gemma":[0.9979789,0.000008210344,0.00001422332,0.001487777,0.00001467587,0.00001874482,0.000002931687,0.000003251659,0.0004712756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07244469,"threshold_uncertainty_score":0.9999225,"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."}}