{"id":"W4380758050","doi":"10.1016/j.advwatres.2023.104488","title":"A consistent multi-resolution particle method for fluid-driven granular dynamics","year":2023,"lang":"en","type":"article","venue":"Advances in Water Resources","topic":"Fluid Dynamics Simulations and Interactions","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hydro One (Canada); Polytechnique Montréal","funders":"","keywords":"Multiphysics; Hagen–Poiseuille equation; Mechanics; Smoothed-particle hydrodynamics; Hydrostatic equilibrium; Convergence (economics); Compressibility; Bed load; Sediment transport; Particle (ecology); Flow (mathematics); Viscosity; Granular material; Geology; Geotechnical engineering; Physics; Finite element method; Sediment","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001119123,0.0004786758,0.001034559,0.0007056901,0.0009980025,0.00111625,0.002676679,0.002183625,0.002808579],"category_scores_gemma":[0.002798979,0.0005484623,0.0008980592,0.0008467234,0.0009110352,0.001136328,0.001933213,0.002287378,0.0008184907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000536787,"about_ca_system_score_gemma":0.001631447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004270259,"about_ca_topic_score_gemma":0.003732635,"domain_scores_codex":[0.9996456,0.0001250028,0.00001955542,0.00002669408,0.0001550441,0.00002812671],"domain_scores_gemma":[0.9988844,0.0004883638,0.00005973615,0.0001400623,0.0002842654,0.0001431471],"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":[0.0002755802,0.0003361112,0.001241931,0.0003057859,0.0001792845,0.0003625634,0.0001289559,0.7127848,0.01141662,0.1880097,0.006474032,0.07848465],"study_design_scores_gemma":[0.00002462791,0.000008318847,0.00004162586,0.00000432851,0.000004192064,0.000007125469,0.000002920577,0.9948723,0.0002208785,0.004017581,0.0007899672,0.000006113569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009446826,0.0002868763,0.9863972,0.0003025153,0.0002813893,0.0000988578,0.0001063417,0.0002594635,0.002820539],"genre_scores_gemma":[0.1689713,0.000323691,0.8241793,0.000389829,0.000215908,0.0005411342,0.000272867,0.0005519632,0.004554057],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004270259,"threshold_uncertainty_score":0.009395599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01526961360506972,"score_gpt":0.2901730923588746,"score_spread":0.2749034787538048,"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."}}