Maximal aerobic power in endurance trained and sedentary men and women, 10–74 years of age
Bibliographic record
Abstract
Participation in endurance athletic activities such as running, swimming, and cycling is increasing by people of all ages. It is not unusual for very young and elderly male and female enthusiasts to train for and participate in, short and long distance endurance athletics. The primary purpose of this study was to examine changes in maximal aerobic power (VO2max) in aerobically trained and sedentary untrained men and women over the age range 10-74 yrs. This study is unique in that the data selected for analysis was randomly obtained from 39 years (1970-2009) of peer reviewed published research globally. The data set totaled 18,784 observations from 250 publications and is one of the largest data set of its type. Data was categorized into four sets: aerobically (endurance) trained men, aerobically (endurance) trained women, sedentary untrained men and sedentary untrained women. For each of the four sets, the published VO2maxwas grouped into five-year age periods and the mean VO2maxcalculated for each five-year age period over the age range 10-74 years. The information is important and unique as it provides a benchmark of VO2maxdata from a large global sample of endurance trained and untrained, men and women. This ¿living¿ large database may be queried for analysis providing data on for example; male and female age-related longitudinal changes in aerobic capacity over a lifespan, or differences in aerobic capacity between men and women. Importantly, it definitively proves the inappropriateness of combining male and female physiological data into one group for analysis; a practice which continues to be seen frequently seen in the scientific literature.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".