Сравнительная оценка уровня метаболизма у коров пород Герефорд и Казахская белоголовая
Bibliographic record
Abstract
The health of newborn calves depends on the health of their cow-mothers and colostrum quality which ensure immune protection and high adaptability to environmental factors. The research goal was to study the status and level of metabolism in cows two months before calving. The study was conducted on two farms of the Tselinnniy District of the Altai Region: OOO “Farm” and OOO “Bochkari Аgro”. Two groups of comparable cows were formed for the experiment. The first group was made up of 28 Hereford cows of Canadian breeding and the second group was made up 15 Kazakh White-Headed cows. The status and level of metabolism in the trial animals was compared by 10 biochemical indices. It is found that the indices of carotene, total protein, alkaline reserve, total calcium, inorganic phosphorus, vitamin A, protein fractions and particularly γ-globulin were significantly higher in the Kazakh White-Headed cows as compared to the respective indices of the Hereford cows. The evaluation of the metabolic level in Hereford cows revealed a low level in terms of carotene (in 100% of cows), that of γ-globulin (60.7%), total calcium (75%) and vitamin A (50%). The level of γ-globule in blood serum may be presented as the following logical sequence: high level 39.3% > low level 32.1% > intensive level 14.3% > intermediate and upper intermediate 7.1% for each level. The Kazakh White-Headed cows revealed higher metabolism by all indices including γ-globulin level which may be presented as the logical sequence: high level 53.3% > intermediate 26.6% > upper intensive 20%. The research results show a higher adaptive ability of Kazakh White-Headed cows to environmental factors including nutrition factors.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.014 |
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".