Level of flexibility through sit and reach test from research performed in São Paulo city
Bibliographic record
Abstract
Objective: Examine the level of flexibility of men and women in different ages through the sit and reach test protocol and classify them in accordance with the Canadian Standardized Test of Fitness (CSTF), and from results, draw up a new table that reflects the population analyzed. Methods:16405 individuals physically active and sedentaries were divided in different age groups: 15 to 19 (n = 954), 20 to 29 (n = 2916), 30 to 39 (n = 2161), 40 to 49 (n = 2333), 50 to 59 (n = 2739), 60 to 69 (n = 3195), above 70 (n = 2107). For preparation of the table, the percentiles were calculated for the scores of the test. The percentiles 20, 40, 60 and 80 mentioned above were used as cutoff to generate the ratings: poor, below average, average, above average and excellent, respectively. Results: According to table proposed by CSTF the age groups from 15 to 39 were classified as poor with a flexibility average ranging from 24,805±9,684cm and 26,130± 10,111cm in females and between 21,480±9,905cm and 22.848±9,648cm in males. In the categories from 40 to 69 the average flexibility ranged between 22,768± 9,627cm and 25,396±9,547 in females and between 16,396 ±10,136cm and 19,935±9,192cm in males were classified as below average. Conclusions: Although most of the samples were practicing regular exercise, the average flexibility level presented did not correspond to the average suggested by the CSTF demonstrating the importance of building national reference tables and to establish new normative values as the scale proposed by this work.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".