{"id":"W2768062654","doi":"10.1002/cjce.23071","title":"Numerical simulation of a semi‐industrial scale CFB riser using coarse‐grained DDPM‐EMMS modelling","year":2017,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Granular flow and fluidized beds","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Drag; Mechanics; Particle (ecology); Range (aeronautics); Work (physics); Scale (ratio); Eulerian path; Physics; Computer simulation; Statistical physics; Materials science; Thermodynamics; Geology","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":[0.0003610895,0.0003960021,0.000709644,0.0004131164,0.0005854774,0.0008605049,0.0008007491,0.001413874,0.001604074],"category_scores_gemma":[0.0007559972,0.0003034359,0.000562766,0.0004405114,0.0007678376,0.0003456937,0.0005332294,0.0006449847,0.0001216378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009990081,"about_ca_system_score_gemma":0.001076101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03470779,"about_ca_topic_score_gemma":0.01353876,"domain_scores_codex":[0.9998546,0.0000400327,0.000008533089,0.00002170268,0.00003675314,0.00003839197],"domain_scores_gemma":[0.9995095,0.0002843128,0.00004345516,0.00003594011,0.00007050355,0.00005626761],"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":[0.00004744013,0.00004366466,0.001116161,0.000019159,0.000007756636,0.00005833089,0.00002502321,0.9953374,0.001823426,0.0004858321,0.00005495558,0.000980851],"study_design_scores_gemma":[0.000009789732,0.00001395061,0.0002641649,0.000001148517,0.000001417438,0.000002982879,0.000008878994,0.9993159,0.0002854751,0.0000459863,0.00004811736,0.000002291008],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.964535,0.0001289796,0.02827167,0.0001829995,0.00004831598,0.00007623065,0.0002571494,0.0002198704,0.006279749],"genre_scores_gemma":[0.9919798,0.00004034182,0.007017328,0.00001744937,0.000004167505,0.00003732212,0.00009339142,0.00001069766,0.0007995631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03470779,"threshold_uncertainty_score":0.06901151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03390831891755307,"score_gpt":0.2198524704984879,"score_spread":0.1859441515809348,"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."}}