Modelling Atmospheric Pollution During the Games of the XXVIII Olympiad: Effects on Elite Competitors
Bibliographic record
Abstract
UNLABELLED: The present study investigated the specific atmospheric conditions expected in Athens during the summer of 2004 in relation to the performance of elite athletes. DESIGN: Atmospheric pollution and weather data for the period April 16th to September 30th covering the entire greater Athens area and collected from 1984 to 2003 were used for descriptive statistics and model fitting. The analysis was focused on carbon monoxide (CO), ozone (O3), sulfur dioxide (SO2), nitrogen oxide (NO), nitrogen dioxide (NO2), and particulate matter with a diameter of < 10 microm (PM10). Factor and cluster analysis were used to describe atmospheric pollution in the northern, central, and southern sector of Athens. Generalized estimated equations (GEE) analysis was used to predict mean August 2004 pollutant concentration. Increased concentrations of O3 and PM10 (mean 2003 values: 134.3 +/- 9.3, 44 +/- 1.9 microg/m3, respectively) may generate adverse health and performance effects. The highest O3 values were recorded in the northern Athenian sector during the period June 12th to July 23rd, peaking around mid-day (12:00-18:00) (p < 0.05). The highest PM10 concentrations were recorded in the central Athenian sector during the period August 20th to September 9th, peaking at late afternoon (14:00-22:00) (p < 0.05). Similar concentrations were observed during all days of the week (p > 0.05). GEE approximated mean August 2004 pollutant concentrations similar to: CO: 2.8 (mg/m3), O3: 136, SO2: 24, NO: 134, and NO2: 106 (microg/m3). Concentrations of O3 and PM10 during the XXVIII Olympiad may generate adverse health and performance effects on the cardiovascular function of the elite competitors. (The present manuscript was submitted shortly before the start of the Games and became published after their completion. In this light, the actual pollution rates in Athens during August 2004 are presented in the Note Added in Proof as credence to the statistics used).
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".