Bioaerosols in Peat Moss Processing Plants
Bibliographic record
Abstract
Peat moss is organic matter colonized by large numbers of microorganisms. Storage prior to its processing may result in massive microbial growth. These biological contaminants can become airborne during processing. Our goals were (a) to evaluate concentrations of bioaerosols (inhalable dust, molds, bacteria) in peat moss processing plants that used dust removing systems, and (b) to evaluate the presence of these microorganisms in peat moss. Fourteen plants from Eastern Canada were visited; 3 plants operated all year (all-year mixing plants), and 11 plants functioned only during summer months (seasonal). Air samples were taken throughout the day at different work sites using IOM cassettes for inhalable dust and All-Glass Impinger-30 samplers and Andersen six-stage impactors for microorganisms. Samples of nonprocessed and bagged peat moss (solid material) were also taken and analyzed. A total of 25 work sites for air sampling and 33 solid material samples were analyzed. Air samples contained up to 441.7 mg/m3 of inhalable dust and up to 1.0 x 10(8) CFU/m3 mesophilic molds and 3.3 x 10(5) CFU/m3 bacteria. Seasonal plants were more contaminated with molds and dust than all-year mixing plants. Sieving sites were the most highly contaminated work sites. Airborne dust concentration was significantly correlated with molds and bacteria. Up to 3.8 x 10(7) CFU/g (dry weight) and 4.8 x 10(7) CFU/g (dry weight) molds and bacteria, respectively, were found in the solid material samples. Airborne contaminants did not correlate with solid material content. Despite the use of dust removing systems, peat moss processing plants contain very large amounts of microbially contaminated bioaerosols that do not correlate with the quality of the processed peat. Efficiency of dust removing systems could influence the contamination levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".