The impact of 9/11 on the association of ambient air pollution with daily respiratory hospital admissions in a Canada‐US border city, Windsor, Ontario
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The 11 September 2001 (9/11) terrorist attacks in the United States resulted in long lines of trucks at the border crossing in Windsor, Ontario. Public concern about the potential impact of these trucks spewing toxic pollutants into the air drew attention to the need to investigate the impact of 9/11 on the daily levels of air pollutants and respiratory hospitalization. In this study, significant increases in respiratory admissions were found one month and 6 months post-9/11. Mean daily respiratory admission was also significantly higher than the same period one year earlier and one year later. SO(2) and CO concentration levels were found to be generally higher after 9/11 than one year before and immediately before. Relative risk estimates of respiratory hospitalization after 9/11 showed that SO(2) (RR̂ = 1.15 for two-day, RR̂ = 1.18 for three-day, and RR̂ = 1.21 for five-day averages), NO(2) (RR̂ = 1.10 for current day), and COH (RR̂ = 1.09 for current day, RR̂ = 1.10 for two-day average) had the most significant effects after 9/11. These results suggest the need for more stringent regulatory efforts in air quality in the region in response to the changing transportation dynamics at this Canada-US border crossing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it