Effect of implementing a novel calf vitality scoring system and early intervention program on pain management in newborn dairy calves
Bibliographic record
Abstract
Pain management in newborn calves after dystocia and assisted calving is still not addressed by most producers or veterinarians. The calf VIGOR scoring system, developed at the University of Guelph, was designed to be applied within minutes after birth to assesses Visual appearance, Initiation of movement, General responsiveness, Oxygenation, and heart and respiration Rates in calves. The VIGOR scoring system was designed to identify high risk/low vigor calves for the purpose of applying interventions to improve vigor and survivability. In different studies conducted at the University of Guelph it was reported that providing pain management with a non-steroidal anti-inflammatory (meloxicam), shortly after birth, may improve calf vitality, health and performance outcomes, particularly in calves experiencing dystocia. The objective of this study was to conduct a randomized controlled trial to evaluate the effect of implementing a novel program that includes assessment of newborns using the VIGOR scoring system followed by provision of meloxicam to calves with low vigor scores, on outcomes reflecting calf well-being and health.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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) | 0.000 | 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 teacher head, 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".