A seroepidemiological investigation of undifferentiated bovine respiratory disease
Bibliographic record
Abstract
This thesis investigated the statistical association of titres to ' Pasteurella hemolytica, Hemophilus somnus', bovine viral diarrhoea virus and bovine corona virus, with undifferentiated bovine respiratory disease (UBRD) at three feedlots in Ontario, Canada. The prevalence of exposure to the agents prior to arrival at the feedlot and the incidence of infection during the study period were estimated using the "proxy" variables, arrival titre and change in titre. Titres to 'Pasteurella hemolytica ' and bovine viral diarrhoea virus were examined to elucidate their behaviour. However as more is known about the sero-epidemiology of these two organisms they also represented a point of reference for the behaviour of the 'Hemophilus somnus' and bovine corona virus titres. A factorial design was used to randomise vaccination against both 'Hemophilus somnus ' and 'Pasteurella hemolytica'. The nonvaccinated (for each antigen) animals served as monitors of natural infection. Higher arrival titre to all agents were sparing for subsequent disease risk. It was suggested that 'Pasteurella hemolytica' and bovine viral diarrhoea virus were causally related to UBRD because change in titre was associated with increased UBRD risk in this or other studies. For ' Hemophilus somnus' and bovine corona virus, no evidence existed that infection was associated with increased risk of UBRD treatment. Animals treated for UBRD late in the study period tended to show little or no evidence of exposure to 'Hemophilus somnus'. As this was not observed for 'Pasteurella hemolytica' titres, this suggested that exposure to 'Hemophilus somnus' was inhibited in animals receiving additional antimicrobials for UBRD treatment. The conclusion was drawn that 'Hemophilus somnus' and bovine corona virus were not causally related to UBRD occurrence. Higher arrival titres 'Hemophilus somnus' and bovine corona virus may indicate a functioning immune system in these calves, rather than indicating that titres are protective against the specific organism causing subsequent disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".