Bibliographic record
Abstract
The paper "Trade-offs shaping transmission of sylvatic dengue and Zika viruses in monkey hosts" authored by Kathryn A. Hanley, Hélène Cecilia, Sasha R. Azar, et al., was published in Nature Communications on March 27, 2024. The authors are affiliated with Department of Biology, New Mexico State University, Department of Pathology, University of Texas Medical School, among other institutions. This study explores the factors affecting the transmission of Dengue (DENV) and Zika (ZIKV) viruses in monkey hosts. By experimentally infecting Asian ancestral host species (rhesus monkeys) and a New World host species (squirrel monkeys), the study investigated viral replication, innate and adaptive immune responses (natural killer cells and neutralizing antibodies), and transmission to mosquitoes. Results show that ZIKV reached high titers in both hosts and translated to high mosquito transmission rates; in contrast, DENV-2 had lower replication levels, with transmission occurring only when serum viral titers were below or near the detection limit. The study reveals the immune-mediated trade-offs between the duration and intensity of viral replication.
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 | 0.000 | 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) | 0.002 | 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".