A light-weight, high-sensitivity particle spectrometer for PM2.5 aerosol measurements
Bibliographic record
Abstract
A light-weight, low-cost optical particle spectrometer for measurements of aerosol number concentrations and size distributions has been designed, constructed, and demonstrated. The spectrometer is suitable for use on small, unmanned aerial vehicles (UAVs) and in balloon sondes. The spectrometer uses a 405 nm diode laser to count and size individual particles in the size range 140–3000 nm. A compact data system combines custom electronics with a single-board commercial computer. Power consumption is 7W at 9–15 V. 3D printing technology was used in the construction of the instrument to reduce cost, manufacturing complexity, and weight. The resulting Printed Optical Particle Spectrometer (POPS) instrument weighs about 800 g with an approximate materials cost of 2500 USD. Several POPS units have been constructed, tested in the laboratory, and deployed on UAVs. Here we present an overview of the instrument design and construction, laboratory validation data, and field engineering data for POPS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".