A risk-based life cycle assessment of OPAL petrol and BP regular unleaded petrol
Bibliographic record
Abstract
Gasoline sniffing has been a significant health issue in remote communities in many countries, such as Labrador in Canada. In order to reduce the adverse impacts caused by gasoline sniffing on human health, a new less toxic blend of gasoline (OPAL) produced by BP Australia is proposed to be introduced. This study focuses on the estimation of impacts and risks of OPAL on human health and the environment and its comparison to BP regular unleaded petrol (ULP). A risk-based life cycle analysis was conducted. The results show that OPAL is identified to have less adverse impacts on both the environment and human health. In addition, the risks to human health by using OPAL can be regarded as negligible. Moreover, compared to ULP, OPAL proved to have less risk to human health both in carcinogenic and non-carcinogenic categories. Therefore, it can be predicted that the introduction of OPAL would significantly help to reduce the harmful effects caused by gasoline sniffing in remote areas.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".