Evaluating the feasibility of estimating particulate mass emissions of older-model diesel vehicle using smoke opacity measurements
Bibliographic record
Abstract
Real-world emissions of particulate matter (PM) and smoke opacity were studied for an older-model diesel pickup truck during four types of driving tests, namely fixed-point test, snap-acceleration test, road test, and hill road test (uphill/downhill). A portable emissions measurement system (PEMS) and an opacimeter were used to measure real-time concentrations of PM and smoke opacity, respectively, and simultaneously. Correlation analysis showed a significant positive association between PM and opacity, suggesting the feasibility of using an opacimeter to estimate PM mass emissions from diesel vehicles. Additionally, regression analyses were performed to evaluate the relationship between opacity and PM mass concentration. The results of this study indicate that PM emission concentrations from older-model diesel vehicles can be estimated with a reasonable accuracy by using a smoke opacimeter, which is a relatively simple and cost-effective method of emission testing, as an alternative to sophisticated PM measurement instruments.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".