Bibliographic record
Abstract
This study presents a deterministic model fortheoretically assessing the potential impact of an imperfect avianinfluenza vaccine (for domestic birds) in two avian populations onthe transmission dynamics of avian influenza in the domestic andwild birds population. The model is analyzed to gain insightsinto the qualitative features of its associated equilibria. Thisallows the determination of important epidemiological thresholdssuch as the basic reproduction number and a measure for vaccineimpact. A sub-model without vaccination is first considered, whereit is shown that it has a globally-asymptotically stabledisease-free equilibrium whenever a certain reproduction thresholdis less than unity. Unlike the sub-model without vaccination, the model withvaccination undergoes backward bifurcation, a phenomenonassociated with the co-existence of multiple stable equilibria. Inother words, for the model with vaccination, the classicalepidemiological requirement of having the associated reproductionnumber less than unity does not guarantee disease elimination inthe model. It is shown that the possibility of backwardbifurcation occurring decreases with increasing vaccination rate (for susceptible domesticbirds). Further, the study shows that the vaccineimpact (in reducing disease burden) is dependent on the sign of acertain threshold quantity (denoted by $\nabla_{\mathcal P}$). The vaccine willhave positive or no impact if $\nabla_{\mathcal P}$ is less than orequal to unity. Numerical simulations suggest that the prospect of effectivelycontrolling the disease in the avian population increases with increasing vaccine efficacy and coverage.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".