{"id":"W2262045488","doi":"10.4271/2010-01-2113","title":"Tailoring Ethanol High Temperature Ignition by Means of Chemical Additives and Water Content","year":2010,"lang":"en","type":"article","venue":"SAE international journal of fuels and lubricants","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture","keywords":"Ignition system; Ethanol content; Water content; Ethanol; Autoignition temperature; Waste management; Materials science; Combustion; Chemical engineering; Process engineering; Environmental science; Chemistry; Organic chemistry; Engineering; Aerospace engineering","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":[0.00007510286,0.000100983,0.0001739812,0.00009646819,0.00001350996,0.0000173071,0.0001591702,0.00008765081,0.00006120811],"category_scores_gemma":[0.000161027,0.0000729588,0.00003894016,0.00003422883,0.00009789872,0.0001953319,0.00006605953,0.0003999739,6.46971e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001983855,"about_ca_system_score_gemma":0.000007963993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005008615,"about_ca_topic_score_gemma":5.208034e-7,"domain_scores_codex":[0.9992826,0.000005883428,0.0002757224,0.00009850553,0.000227822,0.0001094885],"domain_scores_gemma":[0.9994145,0.00006881136,0.0001275419,0.00005392356,0.0002797843,0.00005542459],"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":[0.00003678694,0.00002788664,0.000236214,0.000009834444,0.0000716854,0.000009862311,0.00006871195,0.00003310044,0.9910889,0.0007701722,0.00009665821,0.007550229],"study_design_scores_gemma":[0.0006449689,0.00004081474,0.0007956473,0.00008580047,0.00001365047,0.0001670665,0.0001545721,0.0001274829,0.9961843,0.001390229,0.0003068222,0.00008863222],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975448,0.0001257391,0.0008704618,0.0009986139,0.0002832448,0.00003195388,0.00005610539,0.00002402215,0.00006502376],"genre_scores_gemma":[0.9971848,0.0001620369,0.002447781,0.00002668975,0.0001181824,0.000002183855,0.00001082851,0.00001024321,0.00003728267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007461597,"threshold_uncertainty_score":0.2975174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129295798483654,"score_gpt":0.2314114753625436,"score_spread":0.220118517377707,"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."}}