A Brief Report of West Nile Virus Neuroinvasive Disease in the Summer of 2012 in Hamilton, Ontario
Bibliographic record
Abstract
West Nile neuroinvasive disease is a severe infectious disease that is associated with a high mortality rate, especially in immunocompromised hosts. Physicians who are aware of its clinical presentations may be able to order diagnostic tests more appropriately and avoid inappropriate treatment. In the present series, the cases of seven patients admitted to Hamilton Health Sciences (Hamilton, Ontario) in the summer of 2012 with a diagnosis of West Nile neuroinvasive disease were retrospectively reviewed based on available medical records. According to the clinical and laboratory criteria published by the Centers for Disease Control and Prevention, five cases were diagnosed as encephalitis, one case as meningitis and one case as meningomyelitis. Patients were managed supportively. Forty-three percent (three of seven) presented with rash, 71% (five of seven) did not report headache despite exhibiting neurological symptoms, 43% (three of seven) did not have fever on presentation and 37.5% of cerebrospinal fluid samples exhibited a neutrophil predominance. The mortality rate in the present series was 14.3% (one of seven), and 57.1% (four of seven) of the patients had residual symptoms on discharge and at follow-up.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".