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West Nile virus in 2006 and 2007: the Canadian Blood Services' experience

2009· article· en· W1899803546 on OpenAlexaffabout
Sheila F. O’Brien, Vito Scalia, E Zuber, Gordon Hawes, Edward C. Alport, Mindy Goldman, Margaret Fearon

Bibliographic record

VenueTransfusion · 2009
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsCanadian Blood ServicesUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsBlood donationsDonationNatMedicineWest Nile virusBlood donorFalse positive paradoxOrgan donationVirologyDemographyFamily medicineImmunologyVirusInternal medicineTransplantation

Abstract

fetched live from OpenAlex

BACKGROUND: The Canadian blood supply has been screened for West Nile virus (WNV) since 2003. A strategy for targeted individual-donation nucleic acid testing (ID-NAT) was implemented in 2004 to identify potentially infectious donations that may be missed by minipool (MP) testing. In 2007, Canada experienced a larger epidemic than in previous years providing an opportunity to evaluate the ID-NAT triggering algorithm in higher-risk areas. STUDY DESIGN AND METHODS: A specially created database and internal-external communication identified regions for targeted ID-NAT using MP and community triggers. WNV-positive donations identified by ID-NAT were reexamined in MP to assess the efficacy of targeted ID-NAT in identifying potentially infectious donations that may have been missed by MP testing. WNV-positive donation data from 2006 and 2007 were analyzed to examine temporal and geographic trends. A telephone survey about symptoms was carried out after the 2007 season. RESULTS: In total 78 WNV-positive donations were identified (66 true-positives and four false-positives being in 2007). Most positive donations were in the late summer, concentrated in the same western provinces as community cases. Fifty-two donations were identified by ID-NAT and 46% were consistently positive in MP. Of the other 54%, 74% were immunoglobulin (Ig)M- and/or IgG-positive. Fifty-six percent of donors experienced mostly mild symptoms before or after donation (but all said they were well at the time of donation). CONCLUSION: WNV-positive donations correspond geographically with the epidemic. MP testing identifies most potentially infectious donations with a smaller potential benefit from targeted ID-NAT. Mild symptoms are common but may not deter donation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.233
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2009
Admission routes2
Has abstractyes

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