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Record W2141800821 · doi:10.1139/z04-050

Age, sex, and season affect the risk of mycoplasmal conjunctivitis in a southeastern house finch population

2004· article· en· W2141800821 on OpenAlexvenueno aff
Sonia Altizer, Andrew K. Davis, Katherine C. Cook, John J. Cherry

Bibliographic record

VenueCanadian Journal of Zoology · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsBiologyMycoplasma gallisepticumOutbreakFinchPopulationJuvenileZoologyEcologySeasonalityHost (biology)DemographyMycoplasmaVirology

Abstract

fetched live from OpenAlex

House finches (Carpodacus mexicanus (Muller, 1776)) in eastern North America have been affected by annual epidemics of an eye disease caused by the bacterium Mycoplasma gallisepticum since 1994. To identify factors associated with seasonal changes in prevalence and variation in host susceptibility, we monitored mycoplasmal conjunctivitis among wild house finches in a region of high prevalence in southeastern North America. We captured 888 birds between August 2001 and December 2003 and observed seasonal outbreaks characterized by rapid increases in prevalence from August to October each year. During periods of high prevalence, infection probability was significantly higher among juveniles than adults, and the severity of conjunctivitis among juvenile females was greater than for any other host category. We found no evidence linking moulting status to elevated infection risk among adult birds. Finally, house finches with conjunctivitis were in poorer condition than birds with no clinical signs of infection, particularly among those with severe infections. Results from this study are consistent with recent reports of seasonal and regional variation in mycoplasmal conjunctivitis and suggest that annual changes in host reproduction, behaviour, and age structure might be important determinants of the timing and magnitude of local epidemics.

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 score0.282
Threshold uncertainty score0.954

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 head0.011
GPT teacher head0.235
Teacher spread0.223 · 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

Citations75
Published2004
Admission routes1
Has abstractyes

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