{"id":"W3206347031","doi":"10.1080/02786826.2021.1971152","title":"Experimental verification of principal losses in a regulatory particulate matter emissions sampling system for aircraft turbine engines","year":2021,"lang":"en","type":"article","venue":"Aerosol Science and Technology","topic":"Advanced Aircraft Design and Technologies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Air Force Research Laboratory; U.S. Air Force; Federal Aviation Administration; U.S. Environmental Protection Agency","keywords":"Particulates; Principal (computer security); Environmental science; Turbine; Sampling (signal processing); Gas turbines; Aerospace engineering; Engineering; Computer science; Chemistry; Mechanical engineering; Telecommunications","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":[0.0001917407,0.0001010241,0.0001599539,0.0001125439,0.0001478988,0.00001389449,0.0002322834,0.0001066841,0.00002921881],"category_scores_gemma":[0.000151497,0.00008926226,0.00001828308,0.0009626303,0.001106474,0.0002105078,0.0002492612,0.00007808342,0.000009620556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000118343,"about_ca_system_score_gemma":0.00003826363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000100882,"about_ca_topic_score_gemma":0.000008577243,"domain_scores_codex":[0.9989089,0.00000729257,0.0002191985,0.0004074556,0.0001698204,0.0002873408],"domain_scores_gemma":[0.9995042,0.00003158812,0.00007162507,0.0003160025,0.00003744824,0.00003914235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00000480433,0.00004606752,0.02312308,0.00001670322,0.000001541787,0.000003669034,0.00006458761,0.0001139561,0.9732435,0.001543131,0.00001680144,0.001822175],"study_design_scores_gemma":[0.0002366188,0.00004991035,0.005900261,0.00004673105,0.000003719819,0.00003312081,0.001018026,0.0009667864,0.9908863,0.0005508265,0.0001980094,0.0001096852],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963126,0.000218607,0.002292196,0.0006575846,0.00005483202,0.0002107532,0.000002667641,0.000106466,0.00014435],"genre_scores_gemma":[0.98649,0.000009794411,0.01332383,0.00002342763,0.000003412803,0.0000899386,0.000001231559,0.000006188095,0.00005215043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01764282,"threshold_uncertainty_score":0.407685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01685909538135234,"score_gpt":0.2631615689038271,"score_spread":0.2463024735224748,"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."}}