Bibliographic record
Abstract
The present study examines the emission levels of particulate matters (PM) from sparkling fireworks and to know the emission characteristics of PM. Particulate matter <2.5 microns (PM2.5) and suspended particulate matter (SPM) were determined while burning six brands of sparkling fireworks. The average PM concentrations before burning were levels of 10 μg/m3, but the average concentrations after burning were 741 μg/m3 for PM2.5 and 810 μg/m3 for SPM. The mean ratio of the concentrations of PM2.5 and SPM after burning in all of the sparkling fireworks was 0.890. The emissions per firework ranged from 6.5 mg to 151 mg for PM2.5, and from 7.1 mg to 160 mg for SPM. The means of the emissions per combustible amount of the firework ranged from 0.017 to 0.066 mg/mg for PM2.5, and from 0.018 to 0.071 mg/mg for SPM. The influences of the burning time, burning rate and combustible amount of the fireworks on the PM emissions were investigated. As a result, PM2.5 and SPM emissions tend to increase with the burning rates. This suggests that the burning rate of firework have an influence on the PM emissions.
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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 | 0.000 | 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 | 0.001 | 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) | 0.008 | 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; both teacher heads agree on what is shown here.
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".