Temperament in beef cattle: Methods of measurement and their relationship to production
Bibliographic record
Abstract
Sebastian, T., Watts, J. M., Stookey, J. M., Buchanan, F. and Waldner, C. 2011. Temperament in beef cattle: methods of measurement and their relationship to production. Can. J. Anim. Sci. 91: 557-565. Temperament is an individual trait influencing an animal's behavioural response to handling. This characteristic likely modulates the response of the animal to environments and social situations, and is perhaps best viewed as a component of its personality. We assessed temperament using three objective measuring tools, to determine if correlations exist between these and a traditional subjective evaluation. The tools used were strain gauges, a “movement measuring device” (MMD), and a chute exit timer. Four hundred steers were used. Exit time was correlated with values recorded with the MMD and absolute strain forces, and MMD values were related to absolute strain forces. When the animals were classified as “calm” or “wild” based on their subjective scoring, these two groups differed in their mean exit times, MMD values and absolute strain forces. The three objective measures yielded statistically correlated results between tests and across repetitions, and therefore may quantify correlated aspects of a personality trait (i.e., temperament). The objective scores were related to the traditional subjective score, but they provide the advantage of eliminating observer bias and may offer better tools for temperament selection. Significant positive relationships of daily gain with subjective score and MMD values indicate that traditional subjective scoring techniques can be replaced with more repeatable objective measures when temperaments are assessed for performance studies.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".