CASE REPORT - TYPHOID AND MALARIA CO-INFECTION -AN INTERESTING FINDINGIN THE INVESTIGATION OF A TROPICAL FEVER
Bibliographic record
Abstract
In the investigation of fever in the tropics, two important diagnoses to be ruled out are typhoid and malaria. Both cause significant morbidity, mortality and economic loss. An estimated 17 million cases of typhoid are reported worldwide each year, resulting in 0.6 million deaths. Seventy five to eighty percent of these cases occur in Asia alone. Malaria affects 1 billion people each year; out of which 1-3 million die. Although caused by very different organisms -one a Gram negative bacilli, the other a protozoa, and transmitted via different mechanisms -ingestion of contaminated food and water and via the bite of an insect vector respectively, both typhoid and malaria share rather similar symptomatology and epidemiology. Malaysia is endemic for both these diseases and one should not be too surprised when faced with a diagnosis of co-infection of typhoid and malaria, as have been described in India and Canada. Here we describe one such case of Salmonella typhi and Plasmodium vivax infection.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".