Concurrent Infections of Three Mosquito Borne Diseases-Dengue, Chikungunya and Malaria
Bibliographic record
Abstract
Kolkata, India is endemic for mosquito borne diseases like dengue, chikungunya and malaria. For monitoring, altogether 252 serum samples of fever cases were examined for dengue specific NS1 antigen and IgM and IgG antibodies and chikungunya specific IgM antibody. Their blood samples were also tested for malarial parasites. Out of 252 cases, 15 (5.95%), 16 (6.34%) and 18 (7.13%) were infected with dengue, chikungunya and malaria respectively. Amongst 15 dengue cases 10 (3.96%) were positive for both dengue IgM and IgG antibodies and 5 (1.98%) for NS1 antigen. Out of 18 malaria victims 14 (5.55%) and 4 (1.58%) were positive for Plasmodium vivax and Plasmodium falciparum respectively. During the present study, one case of concurrent infections of dengue and chikungunya and another case of concurrent infections of dengue, chikungunya and falciparum malaria were detected. Detail case report of the later has been described. This is the first ever report of concurrent infections of dengue, chikungunya and malaria.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".