Fungal Contamination Assessment in Portuguese Elderly Care Centers
Bibliographic record
Abstract
Individuals spend 80-90% of their day indoors and elderly subjects are likely to spend even a greater amount of time indoors. Thus, indoor air pollutants such as bioaerosols may exert a significant impact on this age group. The aim of this study was to characterize fungal contamination within Portuguese elderly care centers. Fungi were measured using conventional as well as molecular methods in bedrooms, living rooms, canteens, storage areas, and outdoors. Bioaerosols were evaluated before and after the microenvironments' occupancy in order to understand the role played by occupancy in fungal contamination. Fungal load results varied from 32 colony-forming units CFU m(-3) in bedrooms to 228 CFU m(-3) in storage areas. Penicillium sp. was the most frequently isolated (38.1%), followed by Aspergillus sp. (16.3%) and Chrysonilia sp. (4.2%). With respect to Aspergillus genus, three different fungal species in indoor air were detected, with A. candidus (62.5%) the most prevalent. On surfaces, 40 different fungal species were isolated and the most frequent was Penicillium sp. (22.2%), followed by Aspergillus sp. (17.3%). Real-time polymerase chain reaction did not detect the presence of A. fumigatus complex. Species from Penicillium and Aspergillus genera were the most abundant in air and surfaces. The species A. fumigatus was present in 12.5% of all indoor microenvironments assessed. The living room was the indoor microenvironment with lowest fungal concentration and the storage area was highest.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".