{"id":"W2157131977","doi":"10.2514/6.2012-2926","title":"Aviation Emissions Index Derivation Methodologies from Flight Data, including Black Carbon and Aerosols","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Aircraft Design and Technologies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Index (typography); Aviation; Environmental science; Carbon black; Aeronautics; Aerospace engineering; Computer science; Meteorology; Engineering; Physics; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002816592,0.0001075497,0.0001095217,0.00002515666,0.0001112463,0.00001956894,0.0002326738,0.0001089348,0.0002254685],"category_scores_gemma":[0.0004377181,0.00008413508,0.000009527715,0.0001414851,0.0001634989,0.0007209167,0.0008130748,0.0001037749,0.00003174782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000059943,"about_ca_system_score_gemma":0.000002669834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002683258,"about_ca_topic_score_gemma":0.00004011585,"domain_scores_codex":[0.999186,0.00005521978,0.0001406237,0.0002605828,0.0001442254,0.0002133957],"domain_scores_gemma":[0.9992404,0.0002495739,0.00006754929,0.0003839578,0.000003174473,0.00005534069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001019306,0.00003077141,0.6752552,0.000003449791,0.00001177572,7.054037e-7,0.0004449533,0.0001260392,0.2775287,0.0006778611,0.0008481432,0.0450622],"study_design_scores_gemma":[0.0003737123,0.00003499366,0.7439904,0.00002140233,0.0000337478,0.000003000776,0.001644061,0.009497799,0.1970641,0.04215499,0.004700221,0.0004815697],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7546616,0.000116059,0.2394525,0.0004823778,0.00007657379,0.0001473435,0.000006961466,0.0002838533,0.004772794],"genre_scores_gemma":[0.9173048,0.0000773567,0.08226402,0.0000870864,0.00003014952,0.000006673405,0.00002888118,0.000007303501,0.0001937309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1626433,"threshold_uncertainty_score":0.3430929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1179297388701453,"score_gpt":0.3329027139757327,"score_spread":0.2149729751055874,"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."}}