Additional file 1: of Ambient PM2.5 and risk of emergency room visits for myocardial infarction: impact of regional PM2.5 oxidative potential: a case-crossover study
Bibliographic record
Abstract
(Table S1: Descriptive statistics for myocardial infarction cases in Ontario, Canada; Table S2: Daily concentrations of ambient air pollutants in Ontario, Canada (2004–2011); Table S3: Percent change in risk of emergency room visits for myocardial infarction with PM2.5 and PM2.5 oxidative burden in Ontario, Canada (2004–2011); Table S4: Percent change in risk of emergency room visits for myocardial infarction associated with 3-day mean NO2, O3, and Ox Ontario, Canada (2004–2011); Table S5: Percent change in risk of emergency room visits for myocardial infarction with lag-0 PM2.5 and PM2.5 oxidative burden in Ontario, Canada (2004–2011): evaluation of effect modification by gender; Table S6: Percent change in risk of emergency room visits for myocardial infarction with PM2.5 and PM2.5 oxidative burden in Ontario, Canada (2004–2011): evaluation of effect modification by age; Table S7: Percent change in risk of emergency room visits for myocardial infarction associated with Lag-0 PM2.5 and PM2.5 oxidative burden in Ontario, Canada (2004–2011) with sensitivity analyses including additional adjustment for 3-day mean ambient NO2, O3, Ox, or Ox wt; Table S8: Impact of regional PM2.5 oxidative potential on the relationship between ambient PM2.5 and emergency room visits for myocardial infarction; Table S9: Percent change (95 % CI) in risk of emergency room visits for myocardial infarction associated with PM2.5 across strata of regional OPGSH and daily Ox). (PDF 430 kb)
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 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 | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.686 | 0.034 |
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".