A Systematic Review on the Impact of Vaccination for Respiratory Disease on Antibody Titer Responses, Health, and Performance in Beef and Dairy Cattle
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
Bovine respiratory disease (BRD) is a multifactorial disease complex commonly affecting beef and dairy operations. Vaccination against major BRD-related pathogens is routinely performed for disease prevention; however, uniform reporting of health and performance outcomes is infrequent. Our objective was to evaluate the effect of commercially available BRD-pathogen vaccination on titer response with respect to health or performance in beef and dairy cattle. This study was conducted under Prisma 2020 guidelines for systematic reviews and PRESS guidelines utilizing five databases. Criteria for study inclusion were as follows: research conducted in the USA or Canada, between 1982 and 10 October 2022, on beef or dairy cattle, using a commercially available vaccine labeled for a respiratory pathogen of interest, which evaluated antibody titers alongside either performance or morbidity. A total of 3020 records underwent title and abstract evaluation. Full-text analysis was conducted on 466 reports; 101 studies were included in the final review. Approximately 74% of included studies were beef cattle-based versus 26% dairy cattle-based. This review aimed to assess how vaccination titer responses affect beef and dairy cattle health and performance, but varying study methods made comparisons difficult, highlighting the need for consistent reporting.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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