Metabolic blood profile of beef heifers during oestrous and non‐oestrous states
Bibliographic record
Abstract
Haematological metabolic profiles in heifers could contribute to the development of proxies for oestrous detection and provide clues to further characterize biological changes during oestrus. One hundred and seven beef heifers were observed for oestrous behaviour twice daily for 124 days. Feed intake and productive performance (body weight and composition) traits were measured, and feed efficiency was determined using residual feed intake (kg DM/day). Blood plasma samples were collected when signs of oestrus were observed and every 30 ± 2 days. Heifers were considered in oestrus (n = 71) when plasma progesterone concentrations were <0.6 ng/ml. Least square means of blood metabolic parameters were compared between oestrous and non-oestrous states and within oestrous groups according to performance traits and age. Heifers in oestrus exhibited higher concentrations of alkaline phosphatase, aspartate aminotransferase (AST), beta-hydroxybutyric acid, creatine kinase (CK) and triiodothyronine (T3) than heifers in non-oestrus. Heifers in oestrus revealed lower osmolality and concentrations of calcium, sodium and total protein than during non-oestrus. Younger (and smaller) heifers had greater concentrations of CK, gamma-glutamyl transferase (GGT), glucose and sodium than the older heifers. Heifers with lower fatness had increased osmolality and concentrations of cholesterol, CK, phosphorus, sodium and reduced T3 levels. Feed efficient heifers had greater levels of AST, cholesterol and GGT than inefficient heifers. Blood plasma parameters may be complementary to oestrous detection upon further validation; effects of age, feed efficiency, body size and body composition should be considered to optimize this haematological assessment.
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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".