A survey of current levels of trace minerals and vitamins used in commercial diets by the Brazilian pork industry—a comparative study
Bibliographic record
Abstract
Abstract This study identified the levels of trace minerals and vitamins used in commercial diets by the Brazilian pork industry and compared these levels against the Brazilian reference tables and those from the North American pork industry. Animal feed companies (n = 15) and cooperatives/agro-industries (n = 15) from the Brazilian pork sector participated in this study. Levels of vitamin A, D, E, and K, thiamine, riboflavin, niacin, pantothenic acid, pyridoxine, biotin, folic acid, vitamin B12, choline, vitamin C, cobalt, copper, chromium, iodine, iron, manganese, selenium, and zinc were collected. Data were compiled by feeding phase to determine descriptive statistics. Ratios were calculated comparing the observed levels to those from the Brazilian reference tables and those from the North American pork industry. Average levels of trace minerals and vitamins used by the Brazilian pork industry were between 40% and 240% higher than the recommendations of the Brazilian reference tables. Compared to the North American pork industry, Brazilian levels for trace minerals were overall higher but for water-soluble vitamins they were significantly lower. Large between-companies variations were observed for most of the studied nutrients, especially for water-soluble vitamins. In conclusion, the Brazilian pork industry adds a significant margin of safety for trace minerals and vitamins supplementation. The large between-companies variations, especially for water-soluble vitamins, reflect the limited knowledge available on precise levels of supplementation for trace nutrients for pigs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".