NanoMet, a New Instrument for On-line Size- and Substance- Specific Particle Emission Analysis
Bibliographic record
Abstract
Swiss EPA and European occupational health authorities have sponsored the development of a new sampling and measuring system designed to fulfil future requirements of differentiated particle analysis in field use and for certification purposes. The system suppresses the formation of condensates by applying hot dilution. Solid carbonaceous particles are distinguished from ash particles by means of two different sensors. Particles are size classified by their mobility; their active surface is measured. The measurable size ranges from less than 10 nm to 1 micrometer. The detection limit corresponds to a mass concentration of elemental carbon (EC) of about 0.1 μg/m3. The time resolution of 1 second is suitable for on-line analysis of particulate emission during all types of transient cycles, even no-load acceleration. The system includes a compact diluter with tunable dilution factor from 30 to 3000. The instrument is applicable for engine certification, field control and ambient measurement. Currently it is used for trap specification and field control in Switzerland and in Canadian mines.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".