PREDICTION OF AEROSOL HAZARDS ARISING FROM THE OPENING OF AN ANTHRAX-TAINTED LETTER IN AN OPEN OFFICE ENVIRONMENT USING COMPUTATIONAL FLUID DYNAMICS
Bibliographic record
Abstract
Early experimental work, conducted at Defence R&D Canada–Suffield, measured and characterized the personal and environmental contamination associated with simulated anthrax-tainted letters under a number of different scenarios in order to obtain a better understanding of the physical and biological processes for detecting, assessing, and formulating potential mitigation strategies for managing the risks associated with opening an anthrax-tainted letter. These experimental investigations have been extended in the present study to simulate numerically the contamination from the opening of anthrax-tainted letters in an open office environment using computational fluid dynamics (CFD). A quantity of 0.1 g of Bacillus atropheus (formerly referred to as Bacillus subtilis var globigii (BG)) spores in dry powder form, which was used here as a surrogate species for Bacillus anthracis (anthrax), was released from an opened letter in the experiment. The accuracy of the model for prediction of the spatial distribution of BG spores in the office from the opened letter is assessed qualitatively (and to the extent possible, quantitatively) by detailed comparison with measured BG concentrations obtained under a number of different scenarios, some involving people moving within the office. The observed discrepancy between the numerical predictions and experimental measurements of concentration was probably the result of a number of physical processes which were not accounted for in the numerical simulation. These include air flow leakage from cracks and crevices of the building shell; the dispersion of BG spores in the Heating, Ventilation, and Air Conditioning (HVAC) system; and, the effect of deposition and re-suspension of BG spores from various surfaces in the office environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".