{"id":"W4400607436","doi":"10.1029/2023jf007601","title":"An Attempt to Take Into Account Natural Variability in 1D Bedload Prediction","year":2024,"lang":"en","type":"article","venue":"Journal of Geophysical Research Earth Surface","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"BGC Engineering (Canada)","funders":"Consejo Superior de Investigaciones Científicas; Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement; Office Français de la Biodiversité; Ministerio de Ciencia, Innovación y Universidades","keywords":"Bed load; Monte Carlo method; Nonlinear system; Geology; Flow (mathematics); Statistical physics; Physics; Mechanics; Statistics; Mathematics; Geomorphology; Sediment transport","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":[],"consensus_categories":[],"category_scores_codex":[0.00446742,0.0001208972,0.0002176862,0.0001082003,0.0001203836,0.00008484824,0.0003990075,0.00009554686,0.000775406],"category_scores_gemma":[0.0002741009,0.00009375295,0.00007576231,0.0009227589,0.0002458021,0.0009759816,0.00007867021,0.001261211,0.0004671066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001638265,"about_ca_system_score_gemma":0.000120347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000583049,"about_ca_topic_score_gemma":0.000399859,"domain_scores_codex":[0.9972227,0.0004307128,0.0003840465,0.0003444048,0.00117449,0.0004436877],"domain_scores_gemma":[0.9988924,0.0004901731,0.00003532086,0.0002072304,0.00007680846,0.0002980407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001602385,0.002013635,0.419703,0.0002575238,0.0001087154,0.0007929882,0.007848943,0.05243944,0.4540545,0.0003684491,0.003453578,0.05735681],"study_design_scores_gemma":[0.0004262736,0.001638974,0.9382365,0.0001570799,0.00001625909,0.0000207207,0.0001654842,0.02144385,0.009021895,0.005535289,0.02312272,0.0002149764],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966866,0.0001132756,0.0003976338,0.001894694,0.0002654874,0.0001814188,0.000006147081,0.00001981605,0.0004349322],"genre_scores_gemma":[0.9988979,0.00003739091,0.0005742771,0.00008772411,0.0001658971,0.000003422759,0.000003000395,0.0000102454,0.0002201348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5185335,"threshold_uncertainty_score":0.8490152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01818652469146811,"score_gpt":0.3306369089615261,"score_spread":0.312450384270058,"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."}}