Effect of hydrogenated fat-embedded calcium gluconate on lactation performance in dairy cows
Bibliographic record
Abstract
Hydrogenated fat-embedded calcium gluconate (HFCG), a prebiotic mixture designed to target the hindgut, has improved milk and component yields when supplemented in mid-lactation cows, likely due to improved hindgut health. The objective of this study was to evaluate production responses to HFCG when fed to dairy cattle over a full lactation. Seventy-four Holstein cows (21 primiparous, 53 multiparous) were used in a randomized complete block design comparing supplementation with HFCG (approximately 16 g/day supplement delivering approximately 6.4 g active ingredient) to a negative control from approximately 21 days prior to calving until end of lactation. In multiparous cattle supplemented with HFCG, average daily milk protein yield ( P = 0.037) was increased during the first 8 weeks of lactation, while average daily yields of milk fat, and fat- and energy-corrected milk tended ( P ≤ 0.075) to increase over the same period of time. Increased yields were likely supported by the concurrent increase in dry matter intake ( P = 0.036). Future work is needed to characterize the mode of action of this product within both the hindgut lumen and host, as well as investigate the potential differential responses between primiparous and multiparous animals over the course of lactation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".