Genomics Spurs Rapid Advances in Our Understanding of the Biology of Vascular Wilt Pathogens in the Genus <i>Verticillium</i>
Bibliographic record
Abstract
The availability of genomic sequences of several Verticillium species triggered an explosion of genome-scale investigations of mechanisms fundamental to the Verticillium life cycle and disease process. Comparative genomics studies have revealed evolutionary mechanisms, such as hybridization and interchromosomal rearrangements, that have shaped these genomes. Functional analyses of a diverse group of genes encoding virulence factors indicate that successful host xylem colonization relies on specific Verticillium responses to various stresses, including nutrient deficiency and host defense-derived oxidative stress. Regulatory pathways that control responses to changes in nutrient availability also appear to positively control resting structure development. Conversely, resting structure development seems to be repressed by pathways, such as those involving effector secretion, which promote responses to host defenses. The genomics-enabled functional characterization of responses to the challenges presented by the xylem environment, accompanied by identification of novel virulence factors, has rapidly expanded our understanding of niche adaptation in Verticillium species.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".