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Record W2096277117 · doi:10.2987/09-5922.1

Development of Three Additional Culex Species-Specific Polymerase Chain Reaction Primers and Their Application in West Nile Virus Surveillance in Canada

2010· article· en· W2096277117 on OpenAlexafffundabout
Mahmood Iranpour, L. Robbin Lindsay, Antonia Dibernardo

Bibliographic record

VenueJournal of the American Mosquito Control Association · 2010
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsPublic Health Agency of Canada
FundersCanadian Institutes of Health ResearchCenters for Disease Control and Prevention
KeywordsBiologyCulexWest Nile virusPolymerase chain reactionCulex pipiensVirologyCulex quinquefasciatusVeterinary medicineVirusEcologyLarvaAedes aegyptiGeneticsGene

Abstract

fetched live from OpenAlex

In 2002, more than 17,000 mosquito pools collected in Canada (Quebec, Ontario, and Manitoba) were tested at the National Microbiology Laboratory in Winnipeg, Manitoba, for infection with West Nile virus (WNV). Using real-time reverse-transcriptase polymerase chain reaction (RT-PCR), 558 mosquito pools (86% Culex species and 14% other species) had evidence of infection with WNV. Only 30% of the Culex specimens, however, were identified to the species level. In this study, Culex species-specific PCR primers were designed to identify individual mosquitoes and mixed pools of Culex mosquitoes to species. In addition, pools of non-Culex mosquitoes that tested positive for WNV were also screened for Culex DNA to determine the frequency of cross-contamination among mosquitoes of different species. All DNA extracts from 121 Culex and 51 non-Culex pools, previously positive for WNV, were screened, and Culex DNA was detected in approximately 6% of non-Culex pools. This study demonstrates that contamination among mosquito species can occur and emphasizes that precautions should be taken to minimize this potentially confounding effect.

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)0.001
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 score0.596
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.004
GPT teacher head0.200
Teacher spread0.195 · 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

Citations1
Published2010
Admission routes3
Has abstractyes

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