Bibliographic record
Abstract
Dengue is a vector-borne viral disease caused by the flavivirus dengue virus (DENV). Approximately 400 million cases and 22 000 deaths occur due to dengue worldwide each year. It has been reported in more than 100 countries in tropical and subtropical regions. A positive-stranded enveloped RNA virus (DENV) is principally transmitted by Aedes mosquitoes. It has four antigenically distinct serotypes, DENV-1 to DENV-4, with different genotypes and three structural proteins and seven non-structural proteins. Clinical symptoms of dengue range from mild fever to severe dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS), with thrombocytopenia, leucopenia, and increased vascular permeability. Although primary infection causes activation of immune responses against DENV serotypes, the severity of the disease is enhanced via heterotypic infection by various serotypes as well as antibody-dependent enhancement (ADE). The first licensed DENV vaccine was tetravalent CYD Denvaxia, but it has not been approved in all countries. The lack of a suitable animal model, a proper mechanistic study in pathogenesis, and ADE are the main hindrances in vaccine development. This review summarizes the current knowledge on DENV epidemiology, biology, and disease aetiology in the context of prevention and protection from dengue virus disease.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.003 | 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".