PSI-19 Preference grazing evaluation of new forage varieties, and the effect of animal temperament on grazing behaviour
Bibliographic record
Abstract
Abstract In Canada, new forage varieties need not undergo grazing trials before registration and sale. As such, little is known about forage performance under grazing, or how animal preference and temperament affect grazing behaviour. To determine these effects, 6 cool-season forage species including meadow bromegrass (Bromus bieberseinii), orchardgrass (Dactylis glomerate L.), sainfoin (Onobrychis viciifoila ssp. Viciifolia) and three alfalfa varieties (Medicago sativa L.) were established in monoculture and grass-legume binary mixtures (14 treatments) at the Livestock and Forage Centre of Excellence (Saskatchewan, Canada). Forages were seeded in randomized adjacent 0.3 ha (21 × 125 m) strips within each of three, 5 ha paddocks. Sixty-nine Bos taurus crossbred steers (396 ± 34 kg BW) were homogenously allocated to the 3 paddocks for grazing observations. Individual steer temperament was characterized via novel object and corridor tests prior to grazing. The 9 steers showing the most bold or shy temperaments were labelled for identification while grazing. The grazing period length was 19 d, from July 27 to August 15, 2019, with observations made during the first six days. Observers determined forage preference based upon the number of animals grazing each forage type every 30 min for 2 h in the morning and 2 h in the evening. Animal preference did not differ (P > 0.05) between the forage treatments. Yield of grass and legume components did not differ (P > 0.05) between monocultures or binary mixtures (1255 kg ha-1 ± 277 kg ha-1). Steer temperament affected (P < 0.0001) animal distribution, with bold steers traveling further from the center of the paddock than shy steers or average herd animals (P < 0.05). These preliminary results indicate that differences in grazing behaviour were due to individual animal temperament rather than forage preference or performance.
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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) | 0.001 | 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".