{"id":"W2903046091","doi":"10.1002/cjce.23421","title":"Effects of drag force correlations on the mixing and segregation of polydisperse gas‐solid fluidized bed by CFD‐DEM simulation","year":2018,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Granular flow and fluidized beds","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Drag; Fluidization; Fluidized bed; Ternary operation; Mechanics; Thermodynamics; Drag coefficient; Computational fluid dynamics; Mixing (physics); Physics; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005962467,0.0006331387,0.0006892111,0.0006550205,0.0006725249,0.0007575679,0.000512451,0.0007139525,0.0006173321],"category_scores_gemma":[0.001508696,0.0003103767,0.0004658403,0.000491627,0.0005510288,0.0004338982,0.0004010346,0.0005512707,0.00007397614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001366257,"about_ca_system_score_gemma":0.0009278423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02383756,"about_ca_topic_score_gemma":0.009293139,"domain_scores_codex":[0.999773,0.00006768879,0.00001728023,0.0000327642,0.00005661503,0.00005264535],"domain_scores_gemma":[0.9988594,0.000782273,0.0001023413,0.00005238574,0.000145438,0.00005821385],"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":[0.0001980676,0.0001269392,0.007128323,0.00004455525,0.00001965256,0.0001048735,0.00004592484,0.9830724,0.006026954,0.0007281214,0.0001015903,0.002402685],"study_design_scores_gemma":[0.000008723482,0.00002874485,0.0008332003,0.000002683663,0.000003811621,0.000004420563,0.000008084839,0.9964675,0.002550602,0.00003573855,0.00005130748,0.000005190933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917656,0.000153625,0.005947693,0.00006560623,0.00001788942,0.00003120091,0.0001450574,0.0001093791,0.001764076],"genre_scores_gemma":[0.9980258,0.00004483126,0.001695164,0.000007825823,0.0000031575,0.00001149307,0.00006050642,0.000008469692,0.0001427911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02383756,"threshold_uncertainty_score":0.04739761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004139757381936049,"score_gpt":0.1824136329472197,"score_spread":0.1782738755652837,"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."}}