An assessment of immune and stress responsiveness in Holstein-Friesian cows selected for high and low feed conversion efficiency
Bibliographic record
Abstract
The objective of this study was to assess the immune and stress responsiveness of cows identified as extremely high and low feed conversion efficiency phenotypes. The study utilised 16 Holstein-Friesian cows in their third to fourth lactation, and identified as having either extremely high (n = 8) or extremely low (n = 8) feed conversion efficiency. A commercial vaccine was used to induce measurable antibody- and cell-mediated adaptive immune responses and assess general immune responsiveness. Stress responsiveness was assessed by measuring changes in plasma cortisol concentrations in response to yarding and handling. No significant differences in antibody- or cell-mediated immune responsiveness were observed between the extreme high and low feed conversion efficiency phenotypes (P = 0.343 and 0.546, respectively). However, results suggested that plasma cortisol concentrations trended higher in the low feed conversion efficiency phenotype cows than their high feed conversion efficiency counterparts (P = 0.079) 48 h post-yarding and handling. A significant negative correlation was observed between antibody-mediated immune responsiveness and stress responsiveness (r = –0.44, P = 0.043) but not with cell-mediated immune responsiveness (r = 0.135, P = 0.309). This study provides preliminary evidence that cows selected for feed conversion efficiency may have improved stress-coping abilities and immune responsiveness.
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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) | 0.000 | 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".