PSII-B-16 Effect of Calcium Gluconate Embedded in a Hydrogenated fat Matrix on Performance and Carcass Characteristics of Finishing Beef Heifers
Bibliographic record
Abstract
Abstract Gluconate salts have been reported to be metabolized by microbes in the gastrointestinal tract to yield butyrate and consequently enhance its functionality. The objective was to evaluate feed intake, growth, and carcass characteristics for heifers fed increasing doses of hydrogenated fat-embedded calcium gluconate (HFCG). Twenty-one 10-mo Simmental × Limousin beef heifers, blocked by initial BW (323 ± 35.3 kg), were individually fed for 206 d (8.72% barley silage, 87.44% dry-rolled barley grain, and 3.84% mineral and vitamin supplement) and used to evaluate three different levels of HFCG (0.0%, 0.09%, and 0.18%; on DM basis through substitution of barley grain). Dry matter intake was determined weekly, and BW was measured at the start and end of the study and every three weeks. Carcass weight was recorded and carcasses were refrigerated for 13 d. The left ribeye (10th to 13th rib) was excised and evaluated by a certified grader from the Canadian Beef Grading Agency. Inclusion of HFCG did not affect DMI (8.29 kg/d; P = 0.87), ADG (1.37 kg/d; P =0.55), or G:F (0.166 kg/kg; P = 0.32). Final live BW and carcass weight averaged 630.9 ± 34.99 and 374.1 ± 10.19 kg and were not affected by treatment (P = 0.73 and 0.65, respectively). Dose of HFCG did not affect carcass characteristics with average values of 7.0 mm for fat thickness (P = 0.46), 104 cm2 for rib-eye area (P = 0.92), 476 for marbling score (P = 0.94), and 50.3% for retail cut yield (P = 0.62). In addition, HFCG did not affect quality grade (P = 0.38) or yield grade (P = 0.86). The present data suggests that the use of HFCG did not affect performance of finishing heifers or carcass quality on beef heifers regardless of dose.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".