Limited Short-Term Effects of Tactile Stimulation on the Welfare of Newborn Nellore Calves
Bibliographic record
Abstract
This study aimed to evaluate the effects of tactile stimulation on calf welfare. A total of 54 Nellore calves were assessed, with 28 of them receiving tactile stimulation (WTS) for ~60 s and 26 serving as a control. Five body movements and seven facial expressions were scored. Heart rates (HRs) were recorded in three situations: when the calves were placed in lateral recumbency (HR1), during identification procedures (HR2), and after completion of identification procedures (HR3). The differences between HR3 and HR1, as well as HR3 and HR2 were calculated. Initial and weaning weights were recorded, and ADG and weaning weights adjusted to 240 days were determined. Tactile stimulation significantly influenced “head movements”, “third eyelid” exposure, “eye-opening”, and “strained nostrils”. Except for “strained nostrils”, WTS calves exhibited higher scores in these behavioral categories. Treatment also influenced the difference between HR3 and HR2 (p < 0.05) and showed a trend for HR3 and the difference between HR3 and HR1 (p < 0.06). A qualitative behavior assessment (QBA) was applied using facial expressions. Two main principal components were identified, PC1 explaining 63.01% of the data variance and reflecting the calves’ emotionality, and PC2 explaining 19.88% and reflecting excitability. Most WTS calves displayed positive emotional states and high excitability, whereas most NTS calves exhibited the opposite. Treatment did not significantly impact PC1 and PC2 indexes and long-term performance indicators (p > 0.05). We conclude that tactile stimulation of newborn Nellore calves during their initial handling has the potential to enhance their short-term welfare, but only to a limited extent.
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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 | 0.001 |
| 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".