Age, sex, and season affect the risk of mycoplasmal conjunctivitis in a southeastern house finch population
Bibliographic record
Abstract
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.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".