{"id":"W2025028837","doi":"10.1021/ie0607548","title":"Using Computational Fluid Dynamics Modeling and Ultrasonic Doppler Velocimetry To Study Pulp Suspension Mixing","year":2007,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Flow Measurement and Analysis","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computational fluid dynamics; Impeller; Mechanics; Fluent; Velocimetry; Particle image velocimetry; Mixing (physics); Rheology; Ultrasonic sensor; Materials science; Laser Doppler velocimetry; Mechanical engineering; Acoustics; Turbulence; Physics; Engineering; Composite material; Blood flow","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002210797,0.0002403061,0.0002712207,0.0003030124,0.0001779114,0.0001366567,0.0002181296,0.000211269,0.00003829251],"category_scores_gemma":[0.0003363515,0.0002771505,0.00005553592,0.001061965,0.00002101863,0.000109567,0.0001057613,0.0008752536,0.000005429776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005545621,"about_ca_system_score_gemma":0.00005125886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000701874,"about_ca_topic_score_gemma":0.00000800991,"domain_scores_codex":[0.9976631,0.00002460021,0.000403685,0.0003537819,0.0008633772,0.0006914106],"domain_scores_gemma":[0.9990659,0.000204123,0.00001617766,0.0002228942,0.0002016704,0.0002891715],"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":[0.00001510982,0.000025775,0.0009681829,0.00002837436,0.00007996341,0.00001823106,0.00009801157,0.673367,0.3244204,0.000002897096,0.00002089672,0.0009552052],"study_design_scores_gemma":[0.0006031406,0.00002143644,0.0001167888,0.00008125528,0.00002753679,0.00001370405,0.0005126104,0.9371418,0.06119572,0.000007420233,0.00001572596,0.0002629111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769765,0.0001234776,0.02218208,0.00002178106,0.0001364085,0.0002619963,0.000005775047,0.0001696018,0.0001223711],"genre_scores_gemma":[0.9984778,0.000004459753,0.0008969388,0.000001828515,0.000501897,0.000006967073,0.00002406859,0.00006169034,0.00002430999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2637748,"threshold_uncertainty_score":0.9999681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1359915792414998,"score_gpt":0.342476797289712,"score_spread":0.2064852180482123,"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."}}