{"id":"W4323044506","doi":"10.3390/en16052420","title":"Modelling the Impacts of Hydrogen–Methane Blend Fuels on a Stationary Power Generation Engine","year":2023,"lang":"en","type":"article","venue":"Energies","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Mitacs","keywords":"Environmental science; Natural gas; Methane; Thermal efficiency; Combustion; Automotive engineering; Nuclear engineering; Waste management; Engineering; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002834544,0.0007493946,0.0005634871,0.0004198284,0.0003967242,0.000922846,0.0007654502,0.001133709,0.001784186],"category_scores_gemma":[0.0005292229,0.000378412,0.0009137875,0.0003778819,0.0003173502,0.000521641,0.0003797641,0.0004965999,0.0003220313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00093088,"about_ca_system_score_gemma":0.0008546078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03042582,"about_ca_topic_score_gemma":0.01977921,"domain_scores_codex":[0.9998677,0.00002195741,0.000008945278,0.00002228395,0.00004167861,0.00003736474],"domain_scores_gemma":[0.9998181,0.0001054276,0.00002016903,0.000009729177,0.00003717685,0.000009415958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001284428,0.00008636592,0.001915893,0.00006690786,0.0000158733,0.00009763161,0.00002556322,0.9870056,0.00870575,0.0002394847,0.00006632902,0.001646175],"study_design_scores_gemma":[0.00001829395,0.0001464327,0.001237112,0.000004835692,0.00001435327,0.00001109663,0.00002738867,0.9924758,0.005756322,0.0000871982,0.0002124826,0.00000877602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9862343,0.0001527034,0.007076656,0.00004818835,0.0000183237,0.00006520113,0.0004100548,0.00009485045,0.005899715],"genre_scores_gemma":[0.9957034,0.0001162841,0.001803064,0.000008863415,0.000002302289,0.00004052555,0.0002232539,0.00001807154,0.002084293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03042582,"threshold_uncertainty_score":0.06049746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02542739069393066,"score_gpt":0.2539449572204847,"score_spread":0.2285175665265541,"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."}}