Bibliographic record
Abstract
Abstract Indoor air quality (IAQ) in schools is important as it directly affects the health, comfort, and learning ability of students and staff. This study assessed the IAQ in ten rooms at St. Peters Catholic Primary School, Sittingbourne, Kent, between February and March 2024. A portable uHoo business air quality monitor was used to assess ambient temperature, relative humidity, total volatile organic compounds (TVOC), formaldehyde, carbon monoxide (CO), carbon dioxide (CO 2 ), particulate matter (PM 2.5 and PM 10 ). The air quality index results revealed means of: temperature (18.45 ± 2.23 °C), relative humidity (57.59 ± 4.32%), CO (0.14 ± 0.11 ppm), CO 2 (737.20 ± 346.87 ppm), TVOC (2148.62 ± 5456.78 ppb), formaldehyde (18.68 ± 67.67 ppb), PM 2.5 (5.82 ± 2.31 µg/m 3 ), and PM 10 (11.23 ± 2.71 µg/m 3 ). The results revealed variations in the diurnal variations in particulate matter (PM 2.5 and PM 10 ) during school hours and significant differences at 10.00 am break time (7.9 µg/m 3 and 13.3 µg/m 3 ), noon lunch time (7.8 µg/m 3 and 12.9 µg/m 3 ) and 3.00 pm end of school (7.5 µg/m 3 , 12.5 µg/m 3 ). This study concludes that PM in this school is, primarily, driven by PM in the local area, not the school. All parameters were within permissible limits, except for TVOC. The school's management should adopt proactive measures, including routine IAQ assessments. This will allow the school to cultivate healthier environments that foster academic excellence.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".