An assessment of energy balance from sugar-based ethanol for fuel-saving and climate policy - the case of an island economy
Bibliographic record
Abstract
The study assesses the efficiency of sugar-based ethanol production in Mauritius using the net energy balance and energy ratio. The findings indicate a positive net energy balance. For every one unit of fossil fuel used, the system returns more than six times in terms of renewable energy from ethanol. The fuel savings and other economic benefits which may be accrued to Mauritius are discussed. The sensitivity analysis shows that the fossil energy consumed in the production of fertilisers and in the transportation of feedstock to factory represents the main components which influence efficiency indicators. Greening the supply chain may enhance the efficiency and sustainability of bio-ethanol production systems. Green strategies may include the use of organic fertilisers, clean technology, and sustainable transportation and land use. The efficiency indicators can also be used to guide the CDM for sugar-based ethanol project.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".