Assessing the Influence of Seasonal Changes on Mould Growth and Indoor Air Quality in Nunavik
Bibliographic record
Abstract
Indoor air pollution and mould growth in buildings pose a significant threat to indoor air quality (IAQ). This study aimed to quantify airborne fungal indicators, including those related to water damage, and describe fungal diversity on mouldy surfaces in 60 residences in Nunavik. Three sampling campaigns were done between 2023 and 2024. Active air and surface samples from visible mouldy areas were collected. Airborne moulds were quantified in the air with qPCR tools and the fungal diversity of the surfaces was described following fungal cultivation and Sanger-type sequencing. Results showed significant differences in fungal biomass indicators between indoor and outdoor airborne fungal indicators with a marked seasonal variation. Surface samples exhibited similar fungal communities across seasons, suggesting that moisture-related factors in the building contribute to the persistent presence of mould. These findings highlight the impact of seasonal variations and building-related factors on fungal growth and IAQ in Nunavik housing.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".