{"id":"W2891308503","doi":"10.1029/2017jf004578","title":"Development and Application of a Large‐Scale, Physically Based, Distributed Suspended Sediment Transport Model on the Fraser River Basin, British Columbia, Canada","year":2018,"lang":"en","type":"article","venue":"Journal of Geophysical Research Earth Surface","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Institute for Climate Solutions; University of Victoria; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hydrology (agriculture); Sediment transport; Structural basin; Tributary; Sediment; Drainage basin; Environmental science; Erosion; Sedimentation; Sedimentary budget; Distributed element model; Infiltration (HVAC); Scale (ratio); Geology; Geomorphology; Meteorology; Geography; Geotechnical engineering","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":[0.0002816222,0.0006799981,0.0004615753,0.0004515596,0.001587495,0.001230781,0.001846957,0.000932111,0.002089618],"category_scores_gemma":[0.0008580989,0.0005143841,0.0004287037,0.0007591539,0.0006246244,0.0003779132,0.0005699185,0.0006844961,0.0001921106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0185893,"about_ca_system_score_gemma":0.01897863,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9839933,"about_ca_topic_score_gemma":0.9720746,"domain_scores_codex":[0.9998766,0.00002112081,0.000005280163,0.00002676006,0.00002743397,0.00004283208],"domain_scores_gemma":[0.9996976,0.0000601415,0.00001954286,0.00001275452,0.0001602132,0.00004984337],"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":[0.00002700184,0.00002781856,0.00399098,0.00001314734,0.00001151604,0.00007403221,0.00003485734,0.9916816,0.0003999982,0.0007721591,0.000695214,0.002271611],"study_design_scores_gemma":[0.00002258785,0.000007981779,0.002117143,0.000004544399,0.000008314361,0.000004463354,0.00005213263,0.9970753,0.0001361075,0.0001284244,0.000434559,0.000008387742],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9621462,0.0001722939,0.01208849,0.0006637364,0.00003174528,0.0001820576,0.001989223,0.0003653383,0.02236083],"genre_scores_gemma":[0.9848931,0.0001579671,0.007308117,0.0000551964,0.000004085044,0.00008724394,0.000934976,0.00004268975,0.006516677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0185893,"threshold_uncertainty_score":0.1348755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01320163111185341,"score_gpt":0.2466476776148784,"score_spread":0.233446046503025,"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."}}