{"id":"W1509858209","doi":"10.2172/1015131","title":"Investigation of the Potential for Biofuel Blends in Residual Oil-Fired Power Generation Units as an Emissions Reduction Strategy for New York State","year":2009,"lang":"en","type":"report","venue":"","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Brookhaven National Laboratory; New York State Energy Research and Development Authority; U.S. Department of Energy","keywords":"Biofuel; Fuel oil; Residual oil; Waste management; Environmental science; Biodiesel; Diesel fuel; Renewable energy; NOx; Distillation; Fossil fuel; Engineering; Chemistry; Combustion; Petroleum engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038484,0.0002510979,0.0002673062,0.0001957941,0.00013508,0.0000480458,0.0001634007,0.0003719642,0.00004994434],"category_scores_gemma":[0.00006299865,0.000196428,0.00008093034,0.0004035269,0.0000259163,0.0002161809,0.00001306439,0.0002450657,6.243463e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001468134,"about_ca_system_score_gemma":0.00180839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000409447,"about_ca_topic_score_gemma":0.0002488364,"domain_scores_codex":[0.9985068,0.00003364993,0.0006201044,0.0002703288,0.0003155596,0.0002535974],"domain_scores_gemma":[0.9989987,0.00001593632,0.0001898436,0.000330651,0.0003288098,0.0001360521],"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":[0.0001382008,0.00004753014,0.00009116389,0.0007676591,0.0001104437,9.90698e-7,0.00126024,0.3446404,0.3017619,0.0003122992,0.162398,0.1884711],"study_design_scores_gemma":[0.00413795,0.001721191,0.005969144,0.002275595,0.0004104908,0.0001660143,0.001343446,0.3547472,0.5210827,0.01094099,0.09476861,0.002436658],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881154,0.0007509764,0.002348984,0.0003087265,0.002559209,0.0009169542,0.0002613251,0.0001721339,0.004566306],"genre_scores_gemma":[0.9572017,0.001093789,0.003179784,0.00001736585,0.001604898,0.00009204973,0.001714182,0.0001040171,0.03499228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2193208,"threshold_uncertainty_score":0.8010103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07240294556231341,"score_gpt":0.2873407400716668,"score_spread":0.2149377945093534,"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."}}