Indoor Air Pollution (Carbon Dioxide and Total Volatile Organic Compound) and Pulmonary Disorders in Junior High School Students in Depok, West Java
Bibliographic record
Abstract
Good indoor air quality in the school environment is crucial for health and productivity of the students. Indoor air pollution needs to be taken into consideration, given that one can spend 90% of their time indoor. CO2 and Total VOC is an indoor pollutant that causes pulmonary disorder. This research is to investigate the relationship between exposure of CO2, concentration, total VOC and pulmonary disorder in Junior High School students. This research used cross-sectional design conducted on March - May 2018. The samples were 139 students taken by using simple random sampling. CO2 value was measured by Q-trak, Total VOC was measured by ppbRAE and the lung function value was spirometry. Indoor CO2 concentration in Junior High School of Depok is 478.70 ppm, the average total concentration VOC is 6.4 x 10-3 ppm, % KVP = 72.66, % VEP1 = 74.52 and % VEP1/KVP = 93.97 in average, and the proportion of students with pulmonary disorder is 3.6%. There is no relationship found between exposure of indoor CO2 concentration and total VOC with lung disorder VEP1/KVP (CO2, p = 1.000 and total VOC p = 0.374) since the number of students with lung disorder is low in number while CO2 concentration and the total VOC level is below the listed threshold. This study found no evidence that exposure was related to pulmonary disorder. A healthy and clean living behavior in school environment needs to be improved and further research on other indoor air pollutant parameters and respiratory disorders or degenerative disease should be conducted with different methods.
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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 | 0.000 |
| 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 | 0.001 |
| 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".