Behavioral and Morphological Traits of Nellore Cattle That Can Influence Calf Survival and Performance from Birth to Weaning
Bibliographic record
Abstract
This study aimed to identify behavioral and morphological traits of Nellore cattle that can influence calves’ survival and pre-weaning performance. It was performed in two units of a large-scale cow–calf operation farm located in the Central-West region of Brazil, with 975 cow–calf dyads, by scoring cows’ maternal protective behavior, body condition, horns, udder suspension (US), teat size (TS) and calves’ vigor. TS was used to determine teat symmetry (TSm). The production unit where calves were born, their birth date, sex, and birth (BW) and weaning weights were also recorded. Cow ages at calving and production units were used to categorize the cows into twelve classes (Cage). The Shapiro–Wilk test alongside tables of frequencies were used to determine if continuous and categorical variables followed a normal distribution, respectively. Two datasets were considered in statistical analyses: (i) 975 dyad records were used to identify potential factors influencing calf survivability and (ii) 936 records of weaned calves were used to assess pre-weaning performance. Generalized linear models were used to assess the effect of target traits on the calves’ weight adjusted for 210 days of age (W210, kg) and pre-weaning average daily gain (preADG, kg/day). Tukey’s test was used to compare W210 and preADG means. Pearson’s correlation coefficients were estimated between BW, W210 and preADG. Cage, US and the TSm significantly affected pre-weaning calf performance (p < 0.01). Older cows (independently of the production unit) and those with intermediate US and symmetrical teats weaned heavier calves. As expected, positive and significant correlation was observed between BW and preADG (r = 0.35), which, in turn, was highly correlated with W210 (r = 0.99). We concluded that none of the behavioral and morphological traits influenced calf survivability, but cow age, US and TSm impacted pre-weaning performance, with 8- to 11-year-old cows and those with intermediate US and symmetric teats leading to better calf performance at weaning.
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 | 0.000 | 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".