{"id":"W4410333139","doi":"10.1002/cjce.25757","title":"Effect analysis on the clustering characterization of soot particles in sinusoidal exhaust pipeline for reduced particulate emission by computational fluid dynamics analysis","year":2025,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Indian Institute of Technology Delhi","keywords":"Particulates; Soot; Characterization (materials science); Pipeline (software); Materials science; Computational fluid dynamics; Mechanics; Environmental science; Petroleum engineering; Nanotechnology; Chemistry; Physics; Mechanical engineering; Engineering; Combustion","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":[0.0002055528,0.0003056052,0.0002652351,0.0002917428,0.0003012742,0.0003599167,0.0002384892,0.0003180653,0.0007777876],"category_scores_gemma":[0.0004868041,0.000122807,0.0004018912,0.0002106273,0.00025014,0.00024188,0.0002343152,0.0002092519,0.00008079788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003329314,"about_ca_system_score_gemma":0.0004684459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005666745,"about_ca_topic_score_gemma":0.003511902,"domain_scores_codex":[0.9999243,0.00001292569,0.000004499437,0.00001588287,0.00002837915,0.0000139587],"domain_scores_gemma":[0.9998444,0.00005850763,0.00002339046,0.00001643277,0.00004722056,0.00001004977],"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":[0.000366957,0.0002666482,0.01535476,0.0001993963,0.00003393286,0.0002178718,0.0001242693,0.7754551,0.1814094,0.0020909,0.0004305553,0.02405026],"study_design_scores_gemma":[0.000005123295,0.00007641491,0.002778063,0.00000232878,0.000005291166,0.000007566671,0.00002693914,0.9796191,0.01723869,0.00007756743,0.0001563219,0.000006585985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9651164,0.00007087739,0.03295324,0.00004954508,0.00001410331,0.00003520356,0.0001144976,0.000174401,0.001471469],"genre_scores_gemma":[0.9931774,0.00003997051,0.006334772,0.000005589918,0.000001337639,0.00001974132,0.00006910581,0.00001080547,0.0003412665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005666745,"threshold_uncertainty_score":0.01126748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004669119539653829,"score_gpt":0.2093713412049551,"score_spread":0.2047022216653013,"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."}}