{"id":"W2896734782","doi":"10.1139/tcsme-2018-0071","title":"A numerical approach for determining the resistance of fine mesh filters","year":2018,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Aerosol Filtration and Electrostatic Precipitation","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trojan Technologies (Canada); Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Turbulence; Pressure drop; Filter (signal processing); Mechanics; Filtration (mathematics); Flow (mathematics); Flow resistance; Intensity (physics); Boundary (topology); Flow velocity; Computer simulation; Control theory (sociology); Mathematics; Computer science; Physics; Mathematical analysis; Optics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0001584523,0.00009388882,0.0001376713,0.00001972216,0.0001685201,0.00001039155,0.0001958849,0.00007495651,0.000008172648],"category_scores_gemma":[0.00005210131,0.00007424819,0.0002922132,0.0001965173,0.00004401077,0.00005405201,0.000001510766,0.0001055947,1.545945e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001168877,"about_ca_system_score_gemma":0.00006493644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001466827,"about_ca_topic_score_gemma":0.002300019,"domain_scores_codex":[0.9993829,0.000005214458,0.0002126706,0.00009042594,0.00009117447,0.0002176408],"domain_scores_gemma":[0.9995071,0.0001351035,0.00003259931,0.0001721496,0.00008419409,0.00006887043],"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":[0.0001102334,0.00008727187,0.000009575211,0.001847222,0.001137237,6.363583e-8,0.007320781,0.8279077,0.1094318,0.02904492,0.01376213,0.009341037],"study_design_scores_gemma":[0.0003656521,0.00006032195,0.00003603799,0.00002660487,0.00006544098,6.186138e-7,0.0000770445,0.9480997,0.04965919,0.0001492169,0.00134899,0.0001111344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002055743,0.00002066554,0.9968578,0.0002374037,0.0002021366,0.0004117589,0.0001089738,0.00003927925,0.0000662537],"genre_scores_gemma":[0.9149123,0.000002285951,0.08478485,0.00005108478,0.00004086255,0.0001107819,0.000009555493,0.00002494408,0.00006329469],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9128566,"threshold_uncertainty_score":0.3027753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01230842573267581,"score_gpt":0.2073895006119172,"score_spread":0.1950810748792414,"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."}}