Implementation of a digestible calcium system: Why is it needed and where are we?
Bibliographic record
Abstract
The regulation of blood calcium (Ca) and phosphorus (P) levels are closely intertwined, requiring that their metabolically available supply in the diet be carefully balanced. The majority of the P in plant-based feed ingredients is stored as phytate, which is poorly digestible by broilers, while inorganic P sources also show significant variability in digestibility. For decades, poultry nutritionists have incorporated available P in diet formulation, recognizing that the digestibility of P in feedstuffs is highly variable. In contrast, poultry diets are still formulated on a total Ca (tCa) basis, overlooking the variable digestibility of Ca from different dietary sources. Incorrect assumptions regarding the digestibility of Ca can lead to Ca imbalances, which negatively affect both broiler health and overall performance. Furthermore, the influence of Ca and limestone on phytase efficacy, which plays a critical role in enhancing P availability by breaking down phytate, is highlighted. As the poultry industry moves towards implementing a digestible Ca (dCa) system, the development of accurate prediction equations for limestone digestibility becomes essential. Such an approach not only improves the precision of diet formulation but also enhances overall broiler performance by ensuring a more balanced and metabolically available supply of both Ca and P. Transitioning to a dCa system, in conjunction with phytase use, represents a critical step in optimizing nutrient efficiency and improving sustainability in modern poultry production.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".