Bibliographic record
Abstract
Dear Sir: As an alumnus of the Ontario Veterinary College and former Canadian, I read the Canadian veterinary journals with special interest. Thus, I feel compelled to write concerning the Commentary on “The Principles of Vaccination” that were produced cooperatively by a committee of representatives from the Canadian and American Veterinary Medical Associations (CVMA/AVMA) (Can Vet J 2001;42:845–847). Over the last decade, the veterinary profession has generally become more accepting of the need to reevaluate standard vaccination practices. This stems not only from reports that vaccine-induced immunity is of longer duration than previously realized, but also because of the increased risk of adverse events associated with vaccination (1). The above cited Commentary raises issues with regard to recommendations by myself and other researchers in the field about extending the revaccination interval, and measuring serum antibody titers as an approach to assessing the need for booster vaccinations. As the CVMA/AVMA committee had to deal with these and many related issues during the 2-year review process, the timing of the final report may not have permitted review of the most recent literature. Specifically, while the study of McGaw et al (2) was cited with regard to duration of vaccinal immunity in 122 dogs, our much larger study of 1441 dogs (3) was not mentioned. The conclusions reached in our study differed significantly from the earlier one, in that the high prevalence of adequate serum antibody titers (canine parvovirus, 95.1%; canine distemper virus, 97.6%) suggested that annual revaccination may not be necessary. Since the CVMA/AVMA committee report appeared 1 year after the publication of our study, current readership is likely to assume that comments about the need for more laboratory standardization of titer testing and a lack of definition of minimum protective titers are up-to-date. In fact, several commercial and university reference laboratories offer well-standardized titer testing and interpretive comments, and one in-office testing kit is being marketed. It is unfortunate that the content and message conveyed by the present Commentary appears to dismiss the documented value of this approach by advocating maintenance of the status quo.
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 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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".