Bibliographic record
Abstract
The filtration of aerosols and the behavior of aerosolized particles are less intuitive and more complex than commonly indicated in the medical literature, but once the basic principles are presented, they are not difficult to understand or apply. Particles with diameters close to the most penetrating particle size are clearly the particles of greatest concern, interest, and value in considering the performance of different filtration devices, and this size has been identified as the standard particle size for testing respirators and breathing system filters. Although almost every level of health care now mandates the N95 (NIOSH rating) as the minimum rating for medical respirators, there is no such mandate regarding minimum efficiencies of breathing system filters. At least in North America, it still falls to each individual purchaser to ensure that these standardized tests are performed, because manufacturers adhere to these standards only on a voluntary basis. Government regulations similar to NIOSH 42 CFR 84 are needed for breathing system filters and should include a rating system such as N95, N99, or N100. For breathing system filters, the BFE and VFE tests are misleading and should be abandoned (or even better, banned) in favor of internationally recognized sodium chloride tests. Until then, manufacturers will be hesitant to abandon their BFE and VFE data, which give the appearance of vastly better performance than does the sodium chloride test.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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".