{"id":"W2070310555","doi":"10.1016/j.ces.2005.03.011","title":"Using in-line static mixers to intensify gas–liquid mass transfer processes","year":2005,"lang":"en","type":"article","venue":"Chemical Engineering Science","topic":"Fluid Dynamics and Mixing","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bayer (Canada); Dalhousie University","funders":"","keywords":"Contactor; Mass transfer; Mass transfer coefficient; Oxygen; Static mixer; Mixing (physics); Liquid oxygen; Chemistry; Process engineering; Mechanics; Materials science; Mechanical engineering; Nuclear engineering; Analytical Chemistry (journal); Thermodynamics; Chromatography; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001812198,0.0001752239,0.0001731705,0.0002417981,0.00002596871,0.00004842637,0.0003092486,0.00004939882,0.000007182212],"category_scores_gemma":[0.000228289,0.0001848799,0.00002524227,0.001195172,0.00006310574,0.000262743,0.00003115422,0.0001928244,0.00001010844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002916405,"about_ca_system_score_gemma":0.00006155411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004305279,"about_ca_topic_score_gemma":0.000001876614,"domain_scores_codex":[0.9987262,0.000001333648,0.0002395875,0.0002701723,0.0002321489,0.0005305453],"domain_scores_gemma":[0.9995232,0.00003706449,0.000005005208,0.0001608321,0.00007263268,0.0002012509],"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":[0.00000212593,0.000004056856,0.000003070279,0.00006141616,0.000001244273,0.000002026077,0.0001481664,0.4729049,0.526594,0.00005575151,0.000002967494,0.0002202651],"study_design_scores_gemma":[0.00008220378,0.000009381371,0.00000527022,0.00009538673,0.000002418478,0.000005633966,0.00001286304,0.6058972,0.3936194,0.00000570544,0.0001067852,0.0001577185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7683739,0.00008688859,0.2309664,0.00007959748,0.0001409806,0.00008877389,0.00000255243,0.0001679526,0.00009293525],"genre_scores_gemma":[0.9595059,0.00001150531,0.04029899,0.00007389931,0.00006112355,0.00001028749,0.000001167091,0.00003251385,0.000004622946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.191132,"threshold_uncertainty_score":0.7539183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01234555394114874,"score_gpt":0.2291260310723875,"score_spread":0.2167804771312388,"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."}}