{"id":"W3215214260","doi":"10.1115/icef2021-67909","title":"Ignition Stability Improvement and Emission Reduction via Multiple Ignition Sites Strategy Under Cold Start and Transient Conditions","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Ignition timing; Ignition system; SPARK (programming language); Spark plug; Cold start (automotive); Lean burn; Automotive engineering; Turbocharger; Transient (computer programming); Spark-ignition engine; Homogeneous charge compression ignition; Nuclear engineering; Materials science; Environmental science; Engineering; Mechanical engineering; Computer science; Combustion; Internal combustion engine; Aerospace engineering; Chemistry; Combustion chamber","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":[0.00006325752,0.0001546302,0.000140085,0.00005749604,0.0001149055,0.0000281995,0.0000301773,0.0001166156,0.0001845681],"category_scores_gemma":[0.00006855735,0.0001568251,0.00002862911,0.0001569758,0.00008298637,0.0002716248,0.00003864636,0.0001847096,0.000002171411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001053892,"about_ca_system_score_gemma":0.00001616463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001106318,"about_ca_topic_score_gemma":0.00001087332,"domain_scores_codex":[0.9990969,0.00001707424,0.0002325422,0.0003386064,0.0001318603,0.0001830148],"domain_scores_gemma":[0.9994957,0.00007364614,0.00004053863,0.0001760053,0.0001338302,0.00008021476],"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":[0.00001047565,0.00008509404,0.00004344544,0.00006684179,0.00001575667,0.00000176751,0.00004385855,0.005398153,0.9901536,0.001782943,0.00005055435,0.002347511],"study_design_scores_gemma":[0.0006556141,0.00008569448,0.0005567973,0.00002909687,0.00002768809,0.0000182849,0.0023696,0.04607254,0.944185,0.005727209,0.00007392843,0.0001985676],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7467785,0.00009502169,0.251806,0.0003427516,0.0000384931,0.0002007165,0.0000397547,0.0004613645,0.000237357],"genre_scores_gemma":[0.9957108,0.00008352935,0.003766003,0.00002707284,0.00002061007,0.00005515021,0.0002048111,0.00001601559,0.0001160446],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2489323,"threshold_uncertainty_score":0.6395141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0261619806402435,"score_gpt":0.2469633153476513,"score_spread":0.2208013347074078,"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."}}