Relació entre les velocitats finals assolides per subjectes de sexe masculí en els tests UMTT i UNCa
Bibliographic record
Abstract
Introduccio: El proposit d’aquest estudi fou aplicar 2 tests de camp per valorar la velocitat aerobica maxima a estudiants d’educacio fisica: el test de camp de la Universite de Montreal (UMTT) i el test de camp de la Universidad Nacional de Catamarca (UNCa test), amb l’objectiu de comparar-ne la velocitat, la distancia i el temps acumulat. Material i metode: Es prengueren aleatoriament les mesures de 25 subjectes de sexe masculi, amb el test UMTT i el test UNCa. Els mesuraments es van fer en 2 ocasions. A la primera, es prengueren les mesures antropometriques basiques i s’avalua un test de camp aleatoriament. A la segona s’avalua el segon test de camp. Per analitzar les diferencies i relacions entre les velocitats i altres caracteristiques quantitatives d’ambdos tests s’aplica la prova t per a mostres relacionades i el coeficient de correlacio de Pearson, respectivament. Resultats: Els resultats mostraren que les velocitats assolides a la UMTT foren significativament inferiors a les obtingudes a la UNCa: 13,5 ± 1,4 km·h −1 vs 14,8 ± 1,3 km·h −1 (r = 0,80). Les distancies assolides a la UMTT foren significativament superiors a les obtingudes en el test UNCa: 2.243,2 ± 675,2 m vs 1.810,4 ± 343,7 m (r = 0,81). El temps acumulat en la UMTT fou significativament superior a l’obtingut al test UNCa: 12,0 ± 2,7 min vs 9,8 ± 1,3 min (r = 0,80). Conclusio: Els subjectes assoliren velocitats significativament superiors en el test UNCa en comparacio amb el test UMTT, utilitzant menys temps i distancia.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".