Zika virus, an emerging flavivirus, as a cause of fever and rash in a traveller returning from Central America
Bibliographic record
Abstract
Fever in a returning traveller is a common clinical scenario for physicians in primary and acute care. Differential diagnoses for these patients are generated based on presenting clinical symptoms, travel destinations, potential exposure activities as well as the incubation period of common etiologic agents. In a case of fever and rash in a woman returning to Canada from El Salvador in November 2015, measles, dengue and chikungunya viral infections were queried as possible causes. Subsequent molecular testing using amplification of conserved regions of the flavivirus genome from nasopharyngeal and urine samples was positive, suggesting an active flavivirus infection. Sequencing was significant for the identification of Zika virus, a flavivirus that has only recently become endemic to Brazil and is now emerging throughout Central America. Zika virus should now be included in the differential diagnosis for travelers returning from Central and South America with a febrile illness and rash. To our knowledge this is the first reported case of Zika virus in Canada related to the most recent outbreak in Central America, South America and the Caribbean.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".