{"id":"W2796278114","doi":"10.4271/2018-01-1133","title":"Boosted Current Spark Strategy for Lean Burn Spark Ignition Engines","year":2018,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"University of Windsor; Ford Motor Company","keywords":"SPARK (programming language); Lean burn; Ignition system; Automotive engineering; Current (fluid); Ignition timing; Spark discharge; Materials science; Computer science; Combustion; Engineering; Electrical engineering; Aerospace engineering; Chemistry; Voltage","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004530432,0.001196885,0.001168086,0.0004177178,0.0004610321,0.0001029053,0.001473677,0.001122957,0.0004681332],"category_scores_gemma":[0.002295903,0.001102733,0.0005856577,0.001192052,0.001603321,0.0006474968,0.0004925603,0.001811926,0.0002479061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004950449,"about_ca_system_score_gemma":0.00008445463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009629241,"about_ca_topic_score_gemma":0.003699988,"domain_scores_codex":[0.9945253,0.00005326789,0.001389048,0.001599746,0.0008581582,0.001574553],"domain_scores_gemma":[0.9963845,0.0006790944,0.0003302987,0.001788308,0.0003914337,0.0004263618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000359755,0.0003276318,0.00001662626,0.0001389814,0.00005871332,0.00001427032,0.00001418885,0.0009792269,0.9124706,0.06191376,0.004161545,0.0195447],"study_design_scores_gemma":[0.006031499,0.008284555,0.4332548,0.00202188,0.0005774426,0.0003176199,0.0005708239,0.00006336696,0.02767457,0.08865047,0.4265878,0.005965188],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6915255,0.00686129,0.008567693,0.01906676,0.006224879,0.01555424,0.001598875,0.1152837,0.1353171],"genre_scores_gemma":[0.9841037,0.0003673464,0.0125614,0.0003776534,0.00070868,0.0009416952,0.0001936113,0.0002663004,0.0004796123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.884796,"threshold_uncertainty_score":0.9991423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02777687410378274,"score_gpt":0.2829886784807565,"score_spread":0.2552118043769738,"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."}}