{"id":"W2087178117","doi":"10.1016/j.ces.2007.08.083","title":"Population balance simulation of gas–liquid contacting","year":2007,"lang":"en","type":"article","venue":"Chemical Engineering Science","topic":"Fluid Dynamics and Mixing","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Dalhousie University","keywords":"Breakage; Turbulence; Mechanics; Coalescence (physics); Dissipation; Dispersion (optics); Contactor; Population; Chemistry; Plug flow; Thermodynamics; Materials science; Physics; Optics","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":[0.0003429238,0.00008404886,0.0001058853,0.0001042039,0.00002447935,0.00001338809,0.0001420202,0.00004193724,0.000003058263],"category_scores_gemma":[0.0001991185,0.00009259464,0.00002512759,0.0004295591,0.00003330953,0.0001906738,0.00002311036,0.00009531734,0.000001567594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001144972,"about_ca_system_score_gemma":0.000006976364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005522408,"about_ca_topic_score_gemma":2.114042e-7,"domain_scores_codex":[0.9992093,6.914316e-7,0.0002084335,0.0001277428,0.0001936954,0.0002601385],"domain_scores_gemma":[0.9996533,0.00008322495,0.00002290987,0.0001218454,0.00004591607,0.00007276867],"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":[0.00000163749,0.000001639531,0.0001273131,0.00001952286,8.816694e-7,3.377077e-7,0.00002510609,0.4588172,0.5402502,0.0003073622,3.679957e-7,0.0004484978],"study_design_scores_gemma":[0.00005082309,0.000005102152,0.0009005594,0.0000288361,0.000001369033,0.000001210138,0.000003003943,0.6814766,0.3174388,0.000009372474,0.00001274807,0.00007161032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7989455,0.00003949071,0.2002973,0.000001950011,0.0002032032,0.00003682786,7.779134e-7,0.0001415873,0.0003333044],"genre_scores_gemma":[0.9953842,0.000001673389,0.004542657,0.000003764488,0.00004884592,8.941352e-7,0.00000263226,0.00001338291,0.000001948576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2228114,"threshold_uncertainty_score":0.37759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00502629548223191,"score_gpt":0.2183284326743113,"score_spread":0.2133021371920794,"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."}}