{"id":"W4402814917","doi":"10.1016/j.fuel.2024.133226","title":"Critical experimental evaluation of hydrogen blends with conventional fuels for enhanced power generator performance","year":2024,"lang":"en","type":"article","venue":"Fuel","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ontario Institute of Technology","funders":"University of Ontario Institute of Technology","keywords":"Materials science; Generator (circuit theory); Hydrogen; Nuclear engineering; Power (physics); Process engineering; Chemical engineering; Environmental science; Composite material; Thermodynamics; Chemistry; Physics; Organic chemistry; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0001252767,0.0001125656,0.0001189898,0.00007193529,0.00002309386,0.00001018384,0.00009569045,0.00006520058,0.0003059664],"category_scores_gemma":[0.0001113904,0.0001001637,0.00005166296,0.0001329494,0.00006707434,0.000186672,0.00002595211,0.00009301477,0.00001493938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009568861,"about_ca_system_score_gemma":0.00005646189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.968302e-7,"about_ca_topic_score_gemma":8.807408e-8,"domain_scores_codex":[0.9991645,0.000006581696,0.0001709134,0.0002010157,0.0002956181,0.0001614195],"domain_scores_gemma":[0.9995602,0.00007229247,0.0000198717,0.0001456962,0.0001723731,0.00002955456],"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":[0.00004622389,0.00005404284,0.000008066402,0.0002687984,0.00006160899,9.751469e-7,0.0001239961,0.0435353,0.9171148,0.03671762,0.00009578887,0.001972798],"study_design_scores_gemma":[0.0003516781,0.0001164909,0.00001085026,0.00006830291,0.00002893699,0.000004314198,0.00009002716,0.2410942,0.7568422,0.0008920436,0.000395892,0.0001051354],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7870011,0.002181418,0.208156,0.00009032191,0.0002597223,0.0002581241,0.00003357321,0.0004446825,0.001575044],"genre_scores_gemma":[0.9900737,0.000004820949,0.009411399,0.000008370926,0.00005506638,0.0002711515,0.00002197501,0.00002650559,0.0001269434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2030726,"threshold_uncertainty_score":0.4084558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02169135464108982,"score_gpt":0.3051475850373611,"score_spread":0.2834562303962712,"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."}}