PSLBII-1 Enhancing cattle health and performance through targeted supplement optimization and evaluation
Bibliographic record
Abstract
Abstract Our objective is to evaluate and optimize Bovi-MV formulation through its effect on serum mineral/vitamin (M/V) concentrations in cattle and develop a systems approach to oral M/V supplementation through the lifecycle of beef cattle to determine the best management strategy to help reduce M/V deficiencies in young and mature animals. Cow/calf pairs (n = 300 over 2 yr) and follow the calves to harvest late in yr 2. The research is timed to coincide with typical management handling processes (e.g., vaccination of cows before calving and calf processing after birth, before pasture, at weaning time, on induction to the feedlot, and at reimplanting). The calf herd will be divided at birth into treatment (calves whose dams received BoviMV supplement) and control (~150 calves per group). Vitaferst-Care will be provided to the treatment group at processing (vaccination, antiparasitic application) before going to grass (~ 3 mo of age). Bovi-MV will only be given to the treatment group. All calves will be administered a tracer vaccine to assess their immune response. Blood samples will be collected from all calves for antibody titer testing at weaning (~ 6 mo of age). The treatment calves will also receive a booster dose of Bovi-MV at that time. Approximately 90 d after weaning (~ 9 mo of age) antibody titer will be determined immune response was. Calf morbidity, mortality, and performance (average daily gain) will be monitored in the feedlot. An accredited lab will conduct M/V blood analysis; antibody titer testing will be done at a Lakeland College lab. Based on MV and titer to the Bovi-MV supplement and tracer vaccine, the formulation of the Bovi-MV will be evaluated, and recommendations will be made. Based on results from two previous studies evaluating M/V blood concentrations in cattle (Neonatal supplement and Itchy Cow) in Western Canada, vitamin and mineral concentrations tended to be below optimum values, especially in herds provided supplementation free choice. All cows were deficient in vitamin A at calving, averaging 66.27 ± 2.51 ppb, with 50% having nondetectable concentrations. With vitamin E, 8 animals had nondetectable concentrations, only 8 had sufficient concentrations, and those with detectable concentrations averaged 3.16 ppm ± 2.17. Cows had sufficient iron ug/mL averaging 2.14 ± 1.02 and selenium ug/mL 0.09 ± 0.02. As Cheryl Waldner et al. (2023) reported, 24 to 43% copper deficiency is prevalent in cattle in the southern halves of the three prairie provinces. Armed with this information, this study is the first step in developing a systems approach to year-round management of the cow herd’s vitamin and mineral supplementation.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".