Exposure to carbon monoxide and nitrogen dioxide in enclosed ice arenas
Bibliographic record
Abstract
This article summarises the latest information on the adverse cardiorespiratory effects of exposure to carbon monoxide (CO) and nitrogen dioxide (NO(2)) in enclosed ice rinks. Sources of CO and NO(2) emissions are identified, current standards for these agents, as well as methods of controlling the emissions, dispersion, and evacuation of these toxic gases are presented. A detailed literature search involving 72 references in English and French from research conducted in North America and Europe was used. Material was from peer reviewed journals and other appropriate sources. Air pollutants such as carbon monoxide (CO), and nitrogen dioxide (NO(2)) which are present in enclosed skating facilities, may exacerbate a pre-existing pathogenic condition in those people who spend considerable time in these environments. Considering the popularity of ice hockey, short track speed skating, and figure skating, and the hundreds of hours that a sensitive person may spend each year in these environments, it would seem appropriate to seek more definitive answers to this important health problem. From the findings and conclusions of the research reviewed in this paper, 10 recommendations are listed.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".