Measurement of Airborne Bacteria and Endotoxin Generated During Dental Cleaning
Bibliographic record
Abstract
Dynamic dental instruments generate abundant aerosols in the work environment. Dental unit waterlines (DUWL) support a large microbial population and can be a significant source of bioaerosols generated during dental treatments. This study was conducted to characterize bioaerosol generation during dental treatments performed in standardized conditions. Culture-based method (R2A, and blood agar with and without O2) and fluorescence microscopy were used. Dental cleaning procedures were performed in an isolated treatment room with controlled ventilation rate. Andersen microbial samplers were used to collect culturable bioaerosols generated before (baseline), during, and after 2 hr of dental treatments. Inhalable dust samplers were used to measure total bioaerosols content in dental hygienist's and patients' breathing zones. AGI-30 were used for the collection of the endotoxin. The use of fluorescence microscopy in combination with culture demonstrated that dental staff and patients were exposed to up to 1.86 E+05 bacteria/m(3) generated during treatments. Fortunately, bioaerosols returned to baseline within 2 hr after the dental procedures. The small diameter of the aerosols generated (< 1 microm) suggests that the risk of contact between the aerosolized bacteria and the respiratory system of exposed individuals is likely to occur.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".