Overview of the epidemiology of exercise immunology
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
The application of epidemiological methods to exercise immunology is reviewed briefly, with particular reference to the possible influences of physical activity, exercise and training on susceptibility to upper respiratory infections. Available reports are arbitrarily rated in terms of limiting factors: the quality of the assessment of physical activity, the precision of diagnosis of upper respiratory infection and overall methodology. The pattern of physical activity has often been clearly established but, in part because of the problems associated with the competitive environment, assessments of infection and overall methodology have often been less than optimal. Although there is some evidence that susceptibility to infection is increased by either a single bout of very heavy activity or a period of heavy training, reports are far from unanimous, and in certain respects fail to meet the classical epidemiological criteria of a causal relationship. The issue is important to both the health and the success of the international competitor, and merits definitive investigation, using optimal methods to assess both activity patterns and infection.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 it