West Nile Virus Surveillance and Diagnostic: A Canadian Perspective
Bibliographic record
Abstract
A surveillance program has been in place since 2000 to detect the presence of West Nile virus (WNV) in Canada. Serological assays are most appropriate when monitoring for human disease and undertaking case investigations. Genomic amplification procedures are more commonly used for testing animal and mosquito specimens collected as part of ongoing surveillance efforts. The incursion of WNV into this country was documented for the first time in 2001 when WNV was demonstrated in 12 Ontario health units during the late summer and fall. In 2002 WNV activity was documented by avian surveillance in Ontario by mid-May with subsequent expansion of the virus throughout Ontario and into Quebec, Manitoba, Saskatchewan and Nova Scotia. Human cases were recorded in both Ontario and Quebec in 2002 with approximately 800 to 1000 probable, confirmed and suspect cases detected. The possible recurrence and further spread of WNV to other parts of Canada in 2003 must be anticipated with potential risk to public health. The continued surveillance and monitoring for WNV-associated human illness is necessary and appropriate disease prevention measures need to be in place in 2003.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".