Variables antropométricas y de rendimiento físico en niños y niñas de 10-15 años de edad
Bibliographic record
Abstract
The objective was to determine the relationship and changes in the evolution of basic anthropometric variables and physical performance\ntests in children aged 10-15 years. Seventy-six boys and girls were selected (approximately 50% of each). Six groups were formed according to age.\nAssessments included height, body weight (BW), body mass index (BMI), 0-20 m sprint, vertical jump (CMJ), and an endurance test [Test of the\nUniversity of Montreal (TUM)]. In the distance of 0-10 m. sprint and CMJ, only from 13 years significant differences from the group 10 years were\nreached, and no group improved significantly compared to the group of 12. In the distance of 10-20 m and 0-20 m sprint significant differences from\n12 years to 10 years, and from 13- to 11- years, were observed, but only the 15- years old group did better than the 12- years old. Regarding TUM, a\ntendency to increase the output from 10 to 14 years was observed, but in any case the differences were significant. Relations between the CMJ and TUM\nwith sprint were all significant and negative. Controlling for body weight did not reduce these relationships. The IMC showed positive correlations with\nsprint, and negative with CMJ and TUM, and controlling for height increased these correlations. BMI was stable throughout the age range. The subjects\nwith the highest endurance also tended to be faster and jump higher. The relationship between BMI and endurance was independent of age.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".