{"id":"W4386558456","doi":"10.1007/s40571-023-00651-5","title":"Enhancing an industrial feedwell design and operation using computational fluid dynamics","year":2023,"lang":"en","type":"article","venue":"Computational Particle Mechanics","topic":"Cyclone Separators and Fluid Dynamics","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; University of Saskatchewan","funders":"","keywords":"Computational fluid dynamics; Turbulence; Slurry; Mechanics; Breakup; Volumetric flow rate; Flow (mathematics); Population; Eulerian path; Rheology; Materials science; Simulation; Mechanical engineering; Computer science; Mathematics; Physics; Engineering; Lagrangian; Composite material; Applied mathematics","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":[0.0003755484,0.0001648143,0.0001579587,0.0001001006,0.0002050835,0.0001322836,0.00008300902,0.0001000029,0.00001323343],"category_scores_gemma":[0.00002504137,0.00019491,0.00002937023,0.0003900169,0.00001880279,0.0003209603,0.00004454338,0.0001260641,0.0000423553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001367165,"about_ca_system_score_gemma":0.00006581667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006990219,"about_ca_topic_score_gemma":0.00001303531,"domain_scores_codex":[0.9988653,0.00006636185,0.000320789,0.0002293747,0.0002550464,0.0002631273],"domain_scores_gemma":[0.9995022,0.0001549132,0.00003162704,0.00009222022,0.00008281497,0.0001362086],"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":[0.00001233293,0.00001786361,0.00009196329,0.000009565709,0.00001976533,0.000006091682,0.0001842582,0.9735404,0.006079552,0.01815442,0.00005330513,0.001830504],"study_design_scores_gemma":[0.0004947094,0.00006355772,0.0002706058,0.00001170775,0.00001714028,0.00001976753,0.00009036489,0.9854309,0.001004128,0.01237219,0.000008227264,0.0002166981],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4816787,0.00001891979,0.5177072,0.00002169189,0.000209846,0.0001262717,0.00001273651,0.0002202681,0.000004394216],"genre_scores_gemma":[0.967244,0.000007837045,0.03231897,0.00003564872,0.0001149009,0.000009274329,0.0002198762,0.00004257771,0.000006899316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4855654,"threshold_uncertainty_score":0.7948199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03956474494139108,"score_gpt":0.257558121377993,"score_spread":0.2179933764366019,"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."}}