{"id":"W2063748012","doi":"10.1016/j.ces.2014.07.011","title":"A drag model for filtered Euler–Lagrange simulations of clustered gas–particle suspensions","year":2014,"lang":"en","type":"article","venue":"Chemical Engineering Science","topic":"Granular flow and fluidized beds","field":"Engineering","cited_by":195,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Syncrude","keywords":"Drag; Particle (ecology); Mechanics; Range (aeronautics); Two-fluid model; Fluidization; Physics; Classical mechanics; Drag coefficient; Statistical physics; Fluidized bed; Mathematics; Materials science; Thermodynamics; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001806496,0.0001292095,0.0001783328,0.00007965542,0.00005614774,0.00002574686,0.000283701,0.00005522149,0.000007082843],"category_scores_gemma":[0.0003991515,0.0001301811,0.00007230049,0.0004003269,0.0001077578,0.000158955,0.00004349125,0.00008538624,0.000003787137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003862256,"about_ca_system_score_gemma":0.00001908111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001061069,"about_ca_topic_score_gemma":5.599896e-7,"domain_scores_codex":[0.9990243,0.000002479523,0.000226336,0.0001963744,0.0001890313,0.0003615078],"domain_scores_gemma":[0.9992956,0.0001644977,0.00001659218,0.0002860977,0.00008536556,0.0001518638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002179962,0.000008851544,0.000006912249,0.00003089854,0.000002524165,6.464323e-8,0.00008522611,0.3701786,0.6286815,0.0007906848,0.00003232614,0.000180224],"study_design_scores_gemma":[0.0002350967,0.000006718218,0.00001432879,0.00001692743,0.000007557128,9.450609e-7,0.000001506345,0.6024306,0.3970303,0.0001094155,0.00005360182,0.00009296762],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6155394,0.00002394558,0.383966,0.00002514602,0.0001145729,0.0001045403,0.00001296484,0.0001551804,0.00005819552],"genre_scores_gemma":[0.9803557,0.000001289503,0.01953643,0.00001179173,0.00003971034,0.00001597444,0.000006803981,0.00002318878,0.000009070392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3648163,"threshold_uncertainty_score":0.5308633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01610026818826781,"score_gpt":0.2239051545961266,"score_spread":0.2078048864078588,"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."}}