Bibliographic record
Abstract
Fatty acid methyl ester (FAME), or biodiesel, is a manufactured reaction between methanol and a triglyceride. Biofuel mandates have become increasingly prevalent as efforts to reduce greenhouse gases and emissions and to increase fuel supply security have been stepped up. The United States' Renewable Transport Fuel Obligation and Energy Independence and Security Act, as well as the European Parliament's Directive 2003/30/EC, are among existing legislation. Additionally, legislation is planned by Canadian provincial governments. Biodiesel and ethanol have become two of the world's most widely accepted biofuels today due to mandates such as these. The aviation industry, however, is facing the threat of cross-contamination since biodiesel and jet fuel can be incompatible. The author argues that it is in the best interest of both the aviation industry and passengers to approve higher FAME ppm limits as soon as possible. The author argues that it will be very difficult to manage the current 5 ppm max FAME level, which is considered low. The current level implies a constant threat of refueling-related airport closures and adds significantly to the cost of fuel.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".