Emissions Effects of Alternative Fuels in Light-Duty and Heavy-Duty Vehicles
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<div class="htmlview paragraph">Energy supply and environmental concerns have led to interest in alternative transportation fuels and power-trains. Already, there are significant changes in mainstream gasoline and Diesel formulation to accommodate tighter emissions standards. Some alternative fuels are being promoted as “cleaner” replacements for gasoline and Diesel fuel. There are many research papers which present data on these different alternative fuels, yet it is difficult to compare the fuels with any confidence. The majority of published studies do not use consistent methodology and make many assumptions (which may or may not be reported). Based on an extensive literature review, this study presents emissions results drawn from a smaller number of papers which provide alternative fuel and conventional emissions data in a comparable manner. Both light-duty and heavy-duty vehicles are considered. Reformulated gasoline, compressed natural gas, liquified petroleum gas, methanol-85 and methanol-100 are compared to conventional gasoline and Diesel fuels. The scope of the study includes emissions comparisons on the basis of standard emissions test cycles, low ambient temperature effects, mileage degradation as well as vehicle technology. Additionally, some of the parameters producing variances in emissions values from paper to paper are discussed.</div>
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it