{"id":"W2023410506","doi":"10.1016/j.geomorph.2014.12.013","title":"Coupling channel evolution monitoring and RFID tracking in a large, wandering, gravel-bed river: Insights into sediment routing on geomorphic continuity through a riffle–pool sequence","year":2014,"lang":"en","type":"article","venue":"Geomorphology","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bed load; Geology; Bedform; Hydrology (agriculture); Beach morphodynamics; Sediment transport; Channel (broadcasting); Riffle; Hyperconcentrated flow; Sediment; Geomorphology; Routing (electronic design automation); STREAMS; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000738608,0.000307607,0.0004143482,0.00009226708,0.0004137656,0.00002338073,0.0002415697,0.0002878369,0.0001579846],"category_scores_gemma":[0.00008098103,0.0003058845,0.00004629173,0.0002646343,0.0004543475,0.0003432441,0.0001485658,0.0004948393,0.00007780791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002620243,"about_ca_system_score_gemma":0.00001948271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001950284,"about_ca_topic_score_gemma":0.0009738015,"domain_scores_codex":[0.9977104,0.00009986388,0.0004376364,0.0007697149,0.000277426,0.0007049373],"domain_scores_gemma":[0.9992992,0.0001381823,0.0001841595,0.0002466023,0.00002059269,0.0001112531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002877416,0.0003858888,0.885359,0.00009313739,0.00004865918,0.0002671385,0.01744813,0.03320526,0.05953495,0.002226345,0.0000245009,0.001119262],"study_design_scores_gemma":[0.007903275,0.001280976,0.8399374,0.0005021721,0.0001192784,0.0002013547,0.00123518,0.07841619,0.04649878,0.01972279,0.002590417,0.001592154],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887816,0.000204288,0.009801536,0.0001763976,0.0003373965,0.0003134833,0.000004515375,0.00009397294,0.0002868262],"genre_scores_gemma":[0.9990718,0.0001005445,0.0003552838,0.0002557505,0.000091756,0.00005217202,0.00002578572,0.00002254127,0.00002434213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04542155,"threshold_uncertainty_score":0.9999393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01677494861603729,"score_gpt":0.2502013421075605,"score_spread":0.2334263934915232,"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."}}