Genomewide mutation dynamic within a long-lived individual of <i>Armillaria gallica</i>
Bibliographic record
Abstract
Mutation is the ultimate source of all genetic variation in populations and yet they remain unobservable and buried in the past. Long-lived individuals of Armillaria gallica, a common opportunistic fungal pathogen of tree roots in temperate forests of the northern hemisphere, provide a spatial context for examining the mutational dynamic. Each individual of A. gallica arises in a single mating between two haploid gametes and the resulting diploid then grows vegetatively to occupy a discrete spatial territory often including many adjacent tree root systems. In effect, this leaves a spatial record of growth over time within which mutations can be localized. To identify mutations, the entire genomes of three spatially separated samples of one individual of A. gallica approximately 200 × 60 m were sequenced and compared. In this comparison, mutations and regions of loss of heterozygosity (LOH) were identified then assayed in another 20 isolates from the same individual by conventional PCR and Sanger sequencing. The genotype network of all mutations and LOH were without internal conflict. Further, the spatial pattern of genotypes was nonrandom and appeared to reflect the vegetative expansion leading to the present-day individual. The results reflect the spectrum of spontaneous mutation in nature and provide insight into cellular generation times.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".