Human health effects of traffic-related air pollution (TRAP): a scoping review protocol
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
BACKGROUND: Traffic-related air pollution (TRAP) is one of the major sources of exposure in urban areas and has been associated with a wide range of adverse human health effects. Much of the Canadian population is regularly exposed to TRAP as a result of daily activities (e.g., commuting) and a significant portion of the population resides in close proximity to major roadways. The objective of this scoping review is to develop an evidence map of the epidemiological literature of the human health effects of exposure to TRAP, to support future reviews and assessments by Health Canada. METHODS: Literature searches will be conducted in Ovid EMBASE and Ovid MEDLINE database. DistillerSR will be used to manage the review process. Two reviewers will independently screen the studies in a two-part process (title and abstract; full text) for eligibility. Epidemiological studies and reviews will be included if they report on the human health effects of exposure to TRAP. Data collection will include study design parameters and human health outcomes evaluated in the study. A descriptive analysis will be used to provide a high-level summary of the number of studies evaluating the different types of health effects and cross-tabulations by study design parameters. DISCUSSION: The scoping review will be used to identify subject areas for more detailed review and evaluation of the human health effects of TRAP by the Air Health Effects Assessment Division of Health Canada.
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 | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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