A Novel Personal Air Sampling Device for Collecting Volatile Organic Compounds: A Comparison to Charcoal Tubes and Diffusive Badges
Bibliographic record
Abstract
Evacuated canisters have been used for many years to collect ambient air samples for gases and vapors. Recently, significant interest has arisen in using evacuated canisters for personal breathing zone sampling as an alternative to sorbent sampling. A novel flow control device was designed and built at McGill University. The flow control device was designed to provide a very low flow rate, <0.5 mL/min, to allow a sample to be collected over an extended period of time. Previous experiments run at McGill have shown agreement between the mathematical and empirical models to predict flow rate. The flow control device combined with an evacuated canister (capillary flow control-canister) was used in a series of experiments to evaluate its performance against charcoal tubes and diffusive badges. Air samples of six volatile organic compounds were simultaneously collected in a chamber using the capillary flow control-canister, charcoal tubes, and diffusive badges. Five different concentrations of the six volatile organic compounds were evaluated. The results from the three sampling devices were compared to each other and to concentration values obtained using an online gas chromatograph (GC). Eighty-four samples of each method were collected for each of the six chemicals. Results indicate that the capillary flow control-canister device compares quite favorably to the online GC and to the charcoal tubes, p > 0.05 for most of the tests. The capillary flow control-canister was found to be more accurate for the compounds evaluated, easier to use, and easier to analyze than charcoal tubes and passive dosimeter badges.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".