Is the response to humans consistent over productive life in dairy cows?
Bibliographic record
Abstract
Abstract Dairy cattle have a high level of interaction with humans throughout their productive life. Welfare and productivity are affected if cows find these interactions aversive, so tests assessing fear of humans have been included in welfare assessment protocols. Practicality issues suggest that all animals on large farms cannot be tested. If a sub-sample is chosen, then animal factors affecting the response must be investigated. To assess the effect of age, 114 Holstein cows were tested at regular intervals across their productive lifetime. Animals were tested at 12-15 months of age, first breeding, prior to first calving, then at early, mid and late lactation for 1st and 2nd lactations and into their 3rd lactation. The test involved approaching each cow when standing in the passageway of the barn with sufficient space to retreat. Response was recorded on a 0-8 incremental scale, and several qualitative terms were scored using sliding scales from absence to full presence. There was a significant effect of age on response. Cows became more approachable with increasing age, up until the middle of the first lactation, with no further change beyond this stage. Cows became more at ease and less nervous with increasing age. Individual cow within-group rankings for tests at each stage showed correlation with rankings in the following stage. As this is a single-farm study, further research is necessary to assess interaction of factors such as housing, breed and quality of human handling on the long-term development of fear of humans. However, the results suggest that the age of the animal tested affects the response, and that animals of different age groups should be tested when a sub-sampling is required to assess welfare on large farms.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".