Visiting Hours Impact on Indoor to Outdoor Ratio of Fungi Concentration at Golestan University Hospital in Ahvaz, Iran
Bibliographic record
Abstract
Prevalence of diseases originated from air pollution such as asthma and allergies, can be attributed to the bioaerosols. Bacteria and fungi are the main sources of hospital infections, which cause most of the diseases and mortality. The aim of this study was to determine the ratio of indoor to outdoor fungi concentration, the effect of population and people density on fungi concentration and the relationship between indoor and outdoor environment. In this study, three stations were used: outdoor of the hospital, general indoor and ICU wards of the Ahvaz hospital. These locations were chosen for sampling of the airborne fungi from October to December 2010. The samples were collected in 2 min, flow rate of 28.3 L/min using quick take (SKC Inc., PA, USA), based on the Andersen method.The three dominant culturable fungi genera in sampling stations were Aspergillus, Penicillium, and Cladosporium. The average of total culturable fungi concentration before visiting time was 365.8 CFU m-3 and increased to 578CFU m-3 after visiting time. The indoor to outdoor ratios (I/O) in ICU and internal for fungi before visit were 0.36 and 0.68, respectively. However, these ratios in ICU and internal station for fungi after visit were 0.78 and 0.99, respectively. Following the visit of the visitors, the concentration of fungi available indoor was conspicuously higher (even in the wards in which no visitors were allowed; e.g. ICU, etc). Hence the amount of indoor fungi was affected by the concentration of outdoor fungi and visitors crowd.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".