[Dengue in Peru: a quarter century after its reemergence].
Bibliographic record
Abstract
A health problem each time more frequent and dispersed in tropical and subtropical areas of the world, including Peru where it entered in 1990, is dengue. It is produced by the dengue virus with four serotypes and transmitted by Aedes aegypti, a vector that coexists with humans and whose presence is favored by deficient sanitary, social and economic conditions. Manifestations of severe forms of the disease such as shock and bleeding, are related to the frequent co-circulation of the four serotypes and the emergence of new genotypes such as American/Asian serotype 2. The new classification of the disease by WHO as dengue with or without warning signs and severe dengue, is contributing to more timely diagnosis and treatment, enabling reductions in mortality. Of note is the need to highlight the surveillance of acute febrile illness and Aedes indices that contribute to a timely diagnosis and guide vector control measures through sanitary education and environmental management with community and intersectoral participation, in a creative manner according to ecological niches. An alternative for complementary prevention would be vaccination using tetravalent vaccines whose safety and efficacy must be guaranteed before its use in the population under the framework of comprehensive strategies.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".