{"id":"W1595369099","doi":"10.1002/9781119952497.ch33","title":"Channel Response and Recovery to Changes in Sediment Supply","year":2012,"lang":"en","type":"other","venue":"","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Flume; Channel (broadcasting); Sediment; Sediment transport; Hydrology (agriculture); STREAMS; Environmental science; Geology; Sedimentary budget; Geomorphology; Geotechnical engineering; Computer science; Flow (mathematics); Mechanics","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":[0.0003752599,0.00007738719,0.00017696,0.0004421934,0.0003285664,0.000444406,0.0002334898,0.0003504561,0.003328408],"category_scores_gemma":[0.001922232,0.00008370339,0.0001917344,0.0004261892,0.0004190089,0.0004797727,0.0004272588,0.0002136401,0.0001755275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005518079,"about_ca_system_score_gemma":0.0002927087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01044571,"about_ca_topic_score_gemma":0.0219899,"domain_scores_codex":[0.9998454,0.00003166157,0.000008679291,0.00003619652,0.00002855396,0.0000494296],"domain_scores_gemma":[0.9988897,0.0003823787,0.0003263413,0.0001123719,0.0001689857,0.0001201834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002062248,0.0007247084,0.8221294,0.00014975,0.0001624892,0.001381924,0.001392534,0.05655663,0.05922984,0.002280942,0.002032195,0.05189719],"study_design_scores_gemma":[0.0000280157,0.0004468078,0.9641579,0.000007946227,0.00002185228,0.0001894955,0.0008774295,0.02721347,0.005187856,0.0007801709,0.001059507,0.00002952289],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986993,0.00001702197,0.0002613351,0.00002579676,0.00000106987,0.000004708124,0.00009578664,0.00001056479,0.0008843163],"genre_scores_gemma":[0.9992418,0.00001868613,0.0001301684,0.000009005903,0.000001467229,0.000004316207,0.00008196531,0.00000321587,0.0005094111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01044571,"threshold_uncertainty_score":0.02076983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008965883605255414,"score_gpt":0.2158532732857086,"score_spread":0.2068873896804532,"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."}}