{"id":"W2083314063","doi":"10.1002/hyp.1083","title":"Geometric Brownian motion as a model for river flows","year":2002,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Geometric Brownian motion; Brownian motion; Flow (mathematics); Stochastic modelling; Statistical physics; Motion (physics); Mathematics; Fractional Brownian motion; Applied mathematics; Hydrology (agriculture); Diffusion process; Computer science; Geology; Geometry; Physics; Statistics; Classical mechanics; Geotechnical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002637042,0.001069032,0.001049829,0.001126855,0.0004819988,0.001710889,0.001909703,0.001665518,0.003308914],"category_scores_gemma":[0.006528413,0.0005551309,0.001267932,0.001122526,0.00172351,0.00202721,0.001058103,0.001858274,0.0008724748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001389743,"about_ca_system_score_gemma":0.001072608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005196401,"about_ca_topic_score_gemma":0.002429078,"domain_scores_codex":[0.9988409,0.0005274437,0.00003901681,0.0002221255,0.0002551977,0.0001153681],"domain_scores_gemma":[0.9986129,0.0008034749,0.0002464019,0.0000887079,0.0001596667,0.00008886217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003434195,0.00002776175,0.000858627,0.00002458443,0.00003801257,0.00007712208,0.00005195881,0.7906168,0.0005705117,0.1991263,0.001411121,0.00716277],"study_design_scores_gemma":[0.00001803493,0.00002657788,0.0001903785,0.000006087872,0.00000682605,0.00002374217,0.000004383149,0.9359583,0.00008396438,0.06244225,0.00122843,0.00001103794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09653272,0.000970453,0.8901307,0.002358142,0.0003584025,0.0001084564,0.0004931911,0.0005233509,0.008524505],"genre_scores_gemma":[0.9062354,0.001386586,0.07479901,0.0004076322,0.0003740207,0.0004154359,0.001053788,0.0001357613,0.01519234],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005196401,"threshold_uncertainty_score":0.01394618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03130781069931865,"score_gpt":0.2366169166704321,"score_spread":0.2053091059711134,"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."}}