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 Physical Activity Readiness Questionnaire for Everyone (PAR-Q+) and the electronic Physical Activity Readiness Medical Examination (ePARmed-X+) were created recently to reduce the barriers to physical activity participation for individuals with and without established chronic disease. Our primary purpose was to provide preliminary evidence on the effectiveness of these new forms for pre-participation screening and risk stratification. In particular, we sought to examine the new PAR-Q+ (and ePARmed-X+) risk stratification strategy in comparison to the previous PAR-Q. The new PAR-Q+ and ePARmed-X+ risk stratification and pre-participation strategy reduced significantly the number individuals that were sent for medical referral in comparison to the PAR-Q (i.e., 0.8% vs. 15%, respectively). The reliability of the PAR-Q+ over a three month period was high (r = 0.99). Moreover, the new strategy demonstrated high sensitivity (0.90 (95% CI = 0.77-0.96)) and specificity (1 (95% CI = 0.99-1)) for determining those with and without hypertension, respectively. In conclusion, our preliminary evaluation of the new PAR-Q+ and ePARmed-X+ risk stratification and pre-participation strategy in comparison to the PAR-Q reveals that the new process reduces greatly the barriers to physical activity participation, with a high reliability, sensitivity, and specificity of measurement.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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