Characterization of Microsatellites in Pseudogymnoascus destructans for White-nose Syndrome Genetic Analysis
Bibliographic record
Abstract
(Uploaded by Plazi for the Bat Literature Project) Despite only emerging in the past decade, white-nose syndrome has become among the most devastating wildlife diseases known. The pathogenic fungus Pseudogymnoascus destructans infects hibernating bats and typically leads to high rates of mortality at hibernacula during winter in North America. We developed a set of genetic markers to better differentiate P. destructans isolates. We designed and successfully characterized these 23 microsatellite markers of P. destructans for use in disease ecology and epidemiology research. We validated these loci with DNA extracted from a collection of P. destructans isolates from the US and Canada, as well as from Europe (the likely introduction source based on currently available data). Genetic diversity calculated for each locus and for the multilocus panel as a whole indicates sufficient allelic diversity to differentiate among and between samples from both Europe and North America. Indices of genetic diversity indicate a loss of allelic diversity that is consistent with the recent introduction and rapid spread of an emerging pathogen.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".