Appraisal of Indoor Microbial Pollutants at University Research Labs and Offices under Mediterranean Climate
Bibliographic record
Abstract
Abstract Bacteria and fungi grow indoors when sufficient moisture is available. This study aims to determine the total viable bacterial count and fungi levels and to compare these levels among various science teaching laboratories and staff offices in Gaza city universities. A cross-sectional prospective study was conducted, sixty-five (65) air samples were collected from three local universities using Air Sampler. Auto Ranging Multimeter was used to record humidity and temperature. Air samples with counts of bacteria or fungi more than 500 Colony forming units “CFU”/m3 were considered polluted according to the world health organization (WHO) standards. Among the 65 samples from the three universities, 48 sample (73.8%) had more than 500 colonies/100L. In term of fungal concentration, nine samples (13.8%) exceeded the WHO standards of 500 CFU/m3. The highest percentage of bacterial load in air samples at the three universities (more than 500 CFU/m3) was at IUG with 80.8% due to its old existence, more labs and lab activities. The lowest was at AQU with 61.5% due to less lab and lab activities. The highest percentage of fungal load in air samples at the three universities also were at IUG with 19.2 % and the lowest was at AQU with 7.7%.
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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 | 0.001 | 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) | 0.002 | 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".