The impact of renovation on indoor airborne bacterial and fungal populations
Bibliographic record
Abstract
We undertook an extensive study of population and type of viable microorganisms at several indoor construction sites in a 50-year-old chemical building which housed both laboratory and office spaces. Results were compared to neighbouring public buildings (office and shopping malls), as well as outdoor (green areas and traffic zones) in downtown Montreal, (45 °30′N, 73 °35′W). The highest number of microorganisms was observed in the major shopping street (bacteria: 602,865 cfu/m 3 ; fungi: 109,612 cfu/m 3 ). During moving/construction process, the mean population of airborne bacteria and fungi were 89,281 and 50,386 cfu/m 3 , respectively. Mean bacterial and fungal population in demolished laboratory sites were 37,127 and 17,679 cfu/m 3 , respectively. After the termination of laboratory renovations, continued elevation of airborne taxa population (bacteria: 25,635 cfu/m 3 ; fungi: 6188 cfu/m 3 ) was observed. At the construction site, the 16S rDNA sequence of bacteria isolates, R. equi, was identified as human pathogen and R. jostii RHA1 in an organic demolished laboratory site, with the ability to degrade a variety of xenobiotic compounds such as polychlorinated biphenyls. Our study showed that renovation/construction activities could create a distinct large pool of microorganisms that could be released into indoor environments which may persist even after the completion of renovations. Potential health effects and suggestions for future research are discussed in this paper.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".