Estado nutricional e comportamento alimentar de profissionais de academia de Frederico Westphalen/RS
Bibliographic record
Abstract
The present study aimed to evaluate the nutritional status of gym instructors and check your eating habits. The sample consisted of 18 gym instructors of Frederico Westphalen-RS. To assess the nutritional status, we collected measures of weight, height, arm circumference (AC), waist circumference (WC), hip circumference (HC) and body fat percentage. With these measures we calculated the Body Mass Index (BMI) and waist-to-hip ratio (WHR). The feeding behavior and physical-activity level were analyzed using the standardized questionnaire proposed by the Ministério da Saúde (MS). We found that most professionals had proper values for BMI (61.1%) and for AC (72.2%), WC (61.1%) and WHR (72.2%) classifications. More than half (55.6%) of the samples presented body-fat percentage classified as high and very high. Feeding behavior assessment showed that 77.8% of the professionals under investigation reported proper eating habits. However, only 16.6% had a healthy diet of a nutritional point of view. About 94,4% of participants stated performing regular exercise. Despite the physical appeal and the current demands of the profession, the sample under investigation did not reach high levels of adequacy in relation to nutritional status and eating behavior. Further investigations could elucidate more clearly the nutritional characteristics of these professionals.
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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 | 0.000 |
| 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) | 0.003 | 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".