Observations of a Correlation Between Primary Particle and Aggregate Size for Soot Particles
Why this work is in the frame
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Bibliographic record
Abstract
For decades, soot has been modeled as fractal-like aggregates of nearly equiaxed spherules. Cluster–cluster aggregation simulations, starting from a population of primary particles, give rise to structures that closely match real aerosols of solid particles produced in flames. In such simulations, primary particle size is uncorrelated with aggregate size, as all aggregates contain primary particles drawn from the same population. Aerosol measurements have been interpreted with this geometric model. Examination of transmission electron micrographs of soot samples from various sources shows that primary particle sizes are not well mixed within an aerosol population. Larger aggregates tend to contain larger primary particles and the variation in size is much larger between aggregates than within aggregates. The soot sources considered here are all substantially not well-mixed (aircraft jet engine, inverted diffusion flame, gasoline direct injection engine, heavy-duty compression ignition engine). The observed variations in primary particle size can be explained if soot aggregates are formed and grew by coagulation in small zones of the combustion chamber, prior to dilution and transport (with minimal coagulation) to the sampling system.Copyright 2014 American Association for Aerosol Research
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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 | 0.000 | 0.001 |
| 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 it