MétaCan
Menu
Back to cohort
Record W2182655601 · doi:10.4269/ajtmh.2006.75.1135

USE OF IgG AVIDITY TO INDIRECTLY MONITOR EPIZOOTIC TRANSMISSION OF SIN NOMBRE VIRUS IN DEER MICE (PEROMYSCUS MANICULATUS)

2006· article· en· W2182655601 on OpenAlexaff
David Safronetz, L. Robbin Lindsay, Brian Hjelle, Rafael Medina, Katy Mirowsky-Garcia, Michael Drebot

Bibliographic record

VenueAmerican Journal of Tropical Medicine and Hygiene · 2006
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsUniversity of ManitobaPublic Health Agency of Canada
FundersFogarty International CenterNational Institute of Allergy and Infectious Diseases
KeywordsAvidityPeromyscusBiologyAntibodyVirologyDeer mouseEpizooticOutbreakVirusImmunologyTransmission (telecommunications)Zoology

Abstract

fetched live from OpenAlex

An IgG avidity assay was developed to differentiate deer mice that had recently acquired Sin Nombre virus (SNV) from those that were infected in the distant past. Using this procedure, low avidity antibodies were predominantly detected in experimentally infected deer mice (89.5%) within the first 30 days post-inoculation. The assay was then applied to sera from naturally infected deer mice collected during a field investigation associated with a cluster of hantavirus pulmonary syndrome cases. A higher proportion of seropositive mice collected during the outbreak had serum with low avidity antibodies (16.7%) when compared with mice trapped four months later (5.7%). Sin Nombre virus RNA was detectable in blood in a similar fraction of low- (45%) and high- (38.7%) avidity groups. Non-adult mice were more likely to contain low-avidity antibodies (44.4%) than were adults (9.6%). Our results indicate that the IgG avidity assay shows promise as a tool to better characterize epizootic intensity and to identify factors involved in SNV transmission.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.288
Teacher spread0.263 · 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

Citations14
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Tropical Medicine and HygieneSame topicViral Infections and VectorsFrench-language works237,207