{"id":"W4243097748","doi":"10.1115/1.2055987","title":"Hydrogen Fueled Spark-Ignition Engines Predictive and Experimental Performance","year":2004,"lang":"en","type":"article","venue":"Journal of Engineering for Gas Turbines and Power","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"SPARK (programming language); Combustion; Ignition system; Hydrogen vehicle; Ignition timing; Hydrogen; Spark-ignition engine; Homogeneous charge compression ignition; Automotive engineering; Environmental science; Computer science; Hydrogen fuel; Internal combustion engine; Process engineering; Nuclear engineering; Combustion chamber; Engineering; Aerospace engineering; Chemistry","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":[0.00007763381,0.0001841706,0.0002367118,0.0001508407,0.00003759644,0.00001626954,0.00008527382,0.00008739295,0.000005327179],"category_scores_gemma":[0.000111463,0.0001601812,0.00006414855,0.00009367674,0.00003090574,0.0002987841,0.00003344004,0.0001935508,4.534136e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005767183,"about_ca_system_score_gemma":0.000009318463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.126936e-7,"about_ca_topic_score_gemma":4.050887e-8,"domain_scores_codex":[0.9992983,0.000001716701,0.0002725846,0.0001172778,0.0001117804,0.0001983666],"domain_scores_gemma":[0.9996013,0.00005219149,0.00009397785,0.00008197686,0.00008796077,0.00008257715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001225121,0.00004501,0.00009266254,0.0001215748,0.00008963551,0.000009096513,0.0002635189,0.8404378,0.1568737,0.001390337,0.00002750195,0.0005266168],"study_design_scores_gemma":[0.005016581,0.00172057,0.001035934,0.0006084223,0.0001079944,0.0009296301,0.0004007239,0.1986773,0.7860489,0.001080797,0.003672675,0.0007005352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9266579,0.002060272,0.0706811,0.0001131169,0.0002166511,0.0001098687,0.000006152547,0.0001233049,0.00003165718],"genre_scores_gemma":[0.9862284,0.0001998172,0.01335938,0.00001122693,0.0001351766,0.00001306708,0.000002302066,0.00003121278,0.00001939886],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6417605,"threshold_uncertainty_score":0.6531998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006614036219627206,"score_gpt":0.2144822315200149,"score_spread":0.2078681953003877,"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."}}