Influenza A virus vaccine research conducted in swine from 1990 to May 2018: A scoping review
Bibliographic record
Abstract
BACKGROUND: Influenza A viruses of swine (IAV-S) are a global zoonotic and economic concern. Primary control is through vaccination yet a formal evidence map summarizing vaccine research conducted in pigs is not available. OBJECTIVE: Ten characteristics of English language primary IAV-S vaccine research, conducted at the level of the pig or higher, were charted to identify research gaps, topics for systematic review, and coverage across different publication types. DESIGN: Six online databases and grey literature were searched, without geographic, population, or study type restrictions, and abstracts screened independently and in duplicate for relevant research published between 1990 and May 2018. Full text data was charted by a single reviewer. RESULTS: Over 11,000 unique citations were screened, identifying 376 for charting, including 175 proceedings from 60 conferences, and 170 journal articles from 51 journals. Reported outcomes were heterogeneous with measures of immunity (86%, n = 323) and virus detection (65%, n = 246) reported far more than production metrics (9%, n = 32). Study of transmissibility under conditions of natural exposure (n = 7), use of mathematical modelling (n = 11), and autogenous vaccine research reported in journals (n = 7), was limited. CONCLUSIONS: Most research used challenge trials (n = 219) and may have poor field relevance or suitability for systematic review if the purpose is to inform clinical decisions. Literature on vaccinated breeding herds (n = 89) and weaned pigs (n = 136) is potentially sufficient for systematic review. Research under field conditions is limited, disproportionately reported in conference proceedings versus journal articles, and may be insufficient to support systematic review.
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 | 0.023 | 0.102 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.035 | 0.030 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".