Typical and Atypical Morphology of Non-volatile Particles from a Diesel and Natural Gas Marine Engine
Bibliographic record
Abstract
Non-volatile particle emissions from a marine engine fueled by either diesel or natural gas (NG) blended with diesel pilot gas were investigated via transmission electron microscopy (TEM). The most common particles (> 95% by number) were soot aggregates. These “typical” aggregates exhibited primary particle diameters of 20.7 ± 1.9 and 26.9 ± 1.7 for 100 nm aggregates when diesel and NG fuel were used, respectively. Highly non-uniform aggregates, with distinct groups of smaller and larger monomers, were visible in all of the samples but occurred most frequently with diesel fueling at high loads. The observed “atypical” particles included super-aggregates, small compact aggregates, spheres, mineral-like polyhedral particles, and fibers. Such particles, although rare (averaging 3% by number, as calculated by counting the number of particles for each type depicted in all of the collected images), were found in most of the samples and could have been produced by a variety of mechanisms. For instance, the spheres (approximately 300 nm in diameter) most likely arose from metals within the lubricating oil.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".