{"id":"W2091689820","doi":"10.1016/s0255-2701(01)00167-2","title":"Liquid holdup distribution in packed columns: gamma ray tomography and CFD simulation","year":2002,"lang":"en","type":"article","venue":"Chemical Engineering and Processing - Process Intensification","topic":"Fluid Dynamics and Mixing","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Distributor; Computational fluid dynamics; Packed bed; Inlet; Mechanics; Tomography; Materials science; Volumetric flow rate; Flow (mathematics); Uniform distribution (continuous); Chromatography; Chemistry; Physics; Mathematics; Engineering; Thermodynamics; Optics; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001145419,0.0001964051,0.0001907665,0.0001190081,0.00005117312,0.00009292189,0.00006665519,0.0001558773,0.0000031004],"category_scores_gemma":[0.0001614759,0.0002172723,0.00002270043,0.0004046823,0.00004981656,0.0002669908,0.0000148108,0.0002366185,0.000001338286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005555324,"about_ca_system_score_gemma":0.000004841748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002627308,"about_ca_topic_score_gemma":4.467012e-7,"domain_scores_codex":[0.9990614,0.000004931441,0.0002900809,0.0002781431,0.0001148465,0.0002506143],"domain_scores_gemma":[0.9996012,0.00004759206,0.00003844858,0.0001048496,0.0001180715,0.00008986024],"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":[0.00008547064,0.0001192397,0.001134688,0.003875877,0.00004551157,0.000008034875,0.003914689,0.4646611,0.4491311,0.0004727246,0.0001130966,0.07643843],"study_design_scores_gemma":[0.0002702303,0.00001850527,0.0007414811,0.0002842854,0.00001312249,0.000006815508,0.000062057,0.9892853,0.008768091,0.00006964997,0.0002200766,0.0002603097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9520034,0.002993537,0.0442988,0.00006750003,0.00007287358,0.0001429799,0.000007902078,0.0003468961,0.00006614924],"genre_scores_gemma":[0.9990601,0.0001791972,0.0005326603,0.00001760893,0.00005260367,0.00004248952,0.00007157827,0.00003581543,0.000007969167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5246242,"threshold_uncertainty_score":0.8860109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00948453745071683,"score_gpt":0.2033123891536792,"score_spread":0.1938278517029624,"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."}}