Bibliographic record
Abstract
This study investigated the relationship between atmospheric pollution and emergency hospital admission for asthma among children resident in Turin in the period 1997-1999, using a case-control design. On the basis of the primary diagnosis, pediatric patients (< 15 years old) resident in Turin and admitted for asthma were defined as cases (n(1) = 1,060); age-matched patients admitted for causes other than respiratory diseases or heart diseases were defined as controls (n(2) = 25,523). Nitrogen dioxide (NO(2) in microg/m(3)) and total suspended particulates (TSP in microg/m(3)) were considered as indicators of urban air pollution; sex and age of patient, seasonality, temperature, humidity, solar radiation, and day of admission were considered as principal confounders. Statistical analyses were performed using simple and multiple logistic regression models; the association between emergency admission for asthma and exposure was shown as percentage of risk modification for a 10 microg/m(3) increment of exposure to each pollutant and relative 95% confidence interval. The number of emergency admissions for respiratory causes rose significantly with increased exposure to each pollutant: 2.8% (95% CI, 0.7-4.9%) and 1.8% (95% CI, 0.3-3.2) for a 10 microg/m(3) increment of exposure to NO(2) and TSP, respectively. A significant association was found between increased number of hospital emergency admissions for respiratory causes and exposure to principal urban pollutants in Turin. The study confirms the results reported for other Italian and European cities, using a case-control design.
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.
How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".