Spectrum of Viral Pathogens in Blood of Malaria-Free Ill Travelers Returning to Canada
Bibliographic record
Abstract
Malaria is the most common specific cause of fever in returning travelers, but many other vectorborne infections and viral infections are emerging and increasingly encountered by travelers. We documented common and emerging viral pathogens in malaria-negative specimens from ill travelers returning to Canada. Anonymized, malaria-negative specimens were examined for various viral pathogens by real-time PCR. Samples were positive for herpes simplex viruses 1 or 2 (n = 21, 1.6%), cytomegalovirus (n = 4, 0.3%), Epstein-Barr virus (n = 194, 14.9%), dengue virus types 1-4 (n = 27, 2.1%), chikungunya virus (n = 5, 0.4%), and hepatitis A virus (n = 12, 0.9%). Travel-acquired viral pathogens were documented in >20% of malaria-negative specimens, of which 2.5% were infected with dengue and chikungunya viruses. Our findings support the anecdotal impression that these vectorborne pathogens are emerging among persons who travel from Canada to other countries.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".