An Expert Consensus Study Regarding Management Practices to Prevent Infectious Mortality in Preweaned Beef Calves in Western Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Disease prevention is a cornerstone of herd management for minimizing preweaning calf mortality. However, scientific evidence about the usefulness of practices in herds is scarce. The first objective was for a group of veterinarians to determine which practices are most useful considering their effectiveness, ease of implementation, and economic feasibility. A second objective was for them to define which practices should be included in a tool to facilitate discussions between producers and veterinarians. Expert opinions and consensus were determined using a modified Delphi approach. During two questionnaire rounds, participants scored the effectiveness, ease of implementation, and economic feasibility of each practice. Overall scores for each practice were calculated, and feedback reports were sent to participants between rounds showing the groups' median responses. Consensus on which practices should be included in the tool was targeted during the workshops. Twelve veterinary experts participated. Administering clostridial vaccines and providing calves with colostrum in case they had not nursed were considered practices that were 'always useful for all herds'. However, most practices had intermediate levels of usefulness, and among these, antibiotics were considered the least useful. Nevertheless, all practices discussed during the workshops attained a consensus about being included in the future tool to facilitate on-farm discussions.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it