Bioaerosols concentrations in working areas in biomethanization facilities
Bibliographic record
Abstract
This study sought to fill the gap in information about the type and the concentration of bioaerosols present in the air of biomethanization facilities (BF). Evaluation of bioaerosol composition and concentration was achieved in two biomethanization facilities located in Eastern Canada, during summer and winter. In order to have a thorough understanding of the studied environment, the methodology combined culture of bacteria and molds, qualitiative polymerase chain reaction (qPCR) for specific microorganisms, endotoxin quantification, and next-generation sequencing (NGS) for bacterial diversity. Results revealed that workers in biomethanization facilities are exposed to bioaerosols and pathogenic microorganisms similar to those found in composting plants. However, human exposure levels to bioaerosols are lower in BF than in composting plants. Despite these differences, use of personal protective equipment is recommended to lower the risks of health problems. IMPLICATIONS: Biomethanization is a new technology used in eastern Canada for waste management. In the next few years, it is expected that there will be an expansion of facilities in response of tight governmental regulations. Workers in biomethanization facilities are exposed to various amounts of bioaerosols composed of some harmful microorganisms. Therefore, monitoring this occupational exposure could be an interesting tool for improving worker's health.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".