West Nile virus in Canadian blood donors
Bibliographic record
Abstract
BACKGROUND: Blood donation screening for West Nile virus (WNV) RNA by nucleic acid testing (NAT) was implemented in Canada in July 2003, and 14 WNV RNA-positive donations were identified. Samples were screened in minipools of six donations with a WNV assay (TaqScreen, Roche). Two of the donors were identified by single-donor screening that was initiated in the province of Saskatchewan, which had the highest prevalence of WNV in the country, in early September 2003. STUDY DESIGN AND METHODS: The original 14 samples and follow-up samples (2-35 days after donation), available from 13 of the 14 donors were tested with an in-house, real-time, quantitative WNV NAT assay that was specific for WNV. A Health Canada reference reagent was used for calibration. Immunoglobulin M (IgM) and immunoglobulin G (IgG) levels were determined with commercial enzyme-linked immunosorbent assay kits. RESULTS: All donors tested positive for the presence of WNV with the in-house assay. Two donors, 18 and 19, identified by single-donor testing, had extremely low levels of viremia and that could only be detected in 1:38 or 1:39 replicate tests. The titers of the remaining index samples ranged from below log2.8 (the limit of quantitation) to log4.7 NAT detectable units per mL. Three samples, from Donors 17, 18, and 19, were IgM-positive, whereas samples from Donors 18 and 19 were also IgG-positive. The remaining 10 donors with follow-up samples all seroconverted. CONCLUSION: The 14 WNV donor samples detected by routine screening were confirmed as WNV RNA-positive by a WNV RNA-specific in-house assay and by demonstration of seroconversion in 13 of the 14 donors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".