{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000118386,0.0003080163,0.0002674474,0.0002672024,0.00025011,0.0004541447,0.0002336004,0.0003844069,0.003078093],"category_scores_gemma":[0.0002171327,0.0001587097,0.0003755055,0.0002187667,0.0001203631,0.0004013737,0.0002150331,0.0003207203,0.0003265793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002690407,"about_ca_system_score_gemma":0.0001622004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002965903,"about_ca_topic_score_gemma":0.005150309,"domain_scores_codex":[0.9998908,0.000008563588,0.000005574958,0.00002732256,0.00002909775,0.0000386607],"domain_scores_gemma":[0.9999118,0.00001956329,0.00002407331,0.000008215386,0.00001710683,0.00001917832],"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":[0.001994766,0.0002065998,0.001774416,0.00003875436,0.00002167803,0.00004202532,0.0000275076,0.0003640618,0.9896672,0.00002388293,0.00006395513,0.005775083],"study_design_scores_gemma":[0.00001995511,0.001273977,0.01489168,0.000008700593,0.00003639002,0.00003939626,0.00005958133,0.0009680635,0.9821036,0.00003966032,0.0005512215,0.000007698006],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991769,0.0001134731,0.0002846484,0.00001207296,0.000008429311,0.000003474592,0.00006140891,0.00001164778,0.0003279172],"genre_scores_gemma":[0.9967752,0.0001513213,0.0004066537,0.0000211996,0.000002636021,0.000004059926,0.0001749673,0.00002331007,0.002440653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003078093,"threshold_uncertainty_score":0.0102973,"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."}}