{"id":"W3152108081","doi":"","title":"Simulation of DPM distribution in a long single entry with buoyancy effect","year":2015,"lang":"en","type":"article","venue":"矿业科学技术学报：英文版","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Truck; Diesel fuel; Environmental science; Buoyancy; Computational fluid dynamics; Particulates; Upstream (networking); Airflow; Marine engineering; Diesel engine; Downstream (manufacturing); Environmental engineering; Diesel exhaust; Engineering; Automotive engineering; Meteorology; Waste management; Mechanical engineering; Geography; Operations management; Telecommunications; Mechanics; Aerospace engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000243327,0.0005129055,0.000480871,0.0004792047,0.0006148135,0.0006244387,0.0006254727,0.001248923,0.001570013],"category_scores_gemma":[0.0007614132,0.0002985104,0.0006747713,0.0003365985,0.0004993584,0.000404281,0.0005603851,0.0005847678,0.0001593284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007474369,"about_ca_system_score_gemma":0.0009579348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.039999,"about_ca_topic_score_gemma":0.01958915,"domain_scores_codex":[0.9998693,0.00002026211,0.00000699108,0.00002292221,0.00002797622,0.00005242301],"domain_scores_gemma":[0.9995303,0.0002325405,0.00005284814,0.00002592726,0.00009194502,0.00006634321],"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":[0.00009448793,0.00007743628,0.006689389,0.00002109891,0.000009762847,0.0001909983,0.00004072737,0.9877164,0.003116372,0.0004112657,0.0001278542,0.001504173],"study_design_scores_gemma":[0.00001155728,0.00005685761,0.001106578,0.000002757273,0.000004417629,0.00001214948,0.00005113817,0.9977074,0.000848509,0.00007545712,0.0001182569,0.000004807701],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891869,0.0000408771,0.006584072,0.00007806432,0.00002254707,0.00003651739,0.0002751488,0.00007436769,0.003701484],"genre_scores_gemma":[0.9957125,0.00003861365,0.002656389,0.00001211701,0.000002580729,0.00002787381,0.0002067607,0.00001084813,0.001332288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.039999,"threshold_uncertainty_score":0.07953238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009157540010783144,"score_gpt":0.2223097126988771,"score_spread":0.2131521726880939,"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."}}