{"id":"W2597201551","doi":"10.1038/nature21420","title":"Biofuel blending reduces particle emissions from aircraft engines at cruise conditions","year":2017,"lang":"en","type":"article","venue":"Nature","topic":"Advanced Aircraft Design and Technologies","field":"Environmental Science","cited_by":420,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada; Transport Canada; Deutsche Forschungsgemeinschaft; National Aeronautics and Space Administration","keywords":"Environmental science; Aerosol; Biofuel; Cruise; Aviation; Meteorology; Atmospheric sciences; Aerospace engineering; Waste management; Engineering; Geography; Geology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004346493,0.0001297056,0.000112607,0.00001764647,0.0009663166,0.00005761105,0.000501638,0.0005001362,0.001788938],"category_scores_gemma":[0.0003242138,0.0001059469,0.00005223323,0.00007389121,0.0003216987,0.0003682254,0.0003762163,0.0006555291,0.0004586187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008469104,"about_ca_system_score_gemma":0.000005243557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003591245,"about_ca_topic_score_gemma":0.00007376161,"domain_scores_codex":[0.9991488,0.0000114997,0.0001036357,0.0003086129,0.0001738002,0.0002536798],"domain_scores_gemma":[0.9992003,0.00006352738,0.00008402851,0.0005534058,0.000006348245,0.00009232221],"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":[0.00001251509,0.00007041497,0.1056716,0.000002765874,0.0000183504,0.00005622666,0.0001828594,0.000100298,0.864985,0.0007053344,0.01845827,0.00973633],"study_design_scores_gemma":[0.0004045113,0.00002779645,0.3368995,0.00004619334,0.00002610787,0.0000077935,0.0002098561,0.0004039955,0.5784702,0.03052095,0.05263485,0.0003482637],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906692,0.0004088665,0.0001092469,0.003933205,0.0002774321,0.0001129846,0.0000785463,0.0002754996,0.004135008],"genre_scores_gemma":[0.9937754,0.00007647419,0.003198488,0.0001890335,0.00005834867,0.00001995197,0.0000158628,0.00001251139,0.002653888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2865149,"threshold_uncertainty_score":0.9991236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.014801581208258,"score_gpt":0.2819219073271226,"score_spread":0.2671203261188647,"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."}}