<i>Verticillium</i>Systematics and Evolution: How Confusion Impedes Verticillium Wilt Management and How to Resolve It
Bibliographic record
Abstract
Verticillium wilts are important vascular wilt diseases that affect many crops and ornamentals in different regions of the world. Verticillium wilts are caused by members of the ascomycete genus Verticillium, a small group of 10 species that are related to the agents of anthracnose caused by Colletotrichum species. Verticillium has a long and complicated taxonomic history with controversies about species boundaries and long overlooked cryptic species, which confused and limited our knowledge of the biology of individual species. We first review the taxonomic history of Verticillium, provide an update and explanation of the current system of classification and compile host range and geographic distribution data for individual species from internal transcribed spacer (ITS) GenBank records. Using Verticillium as an example, we show that species names are a poor vehicle for archiving and retrieving information, and that species identifications should always be backed up by DNA sequence data and DNA extracts that are made publicly available. If such a system were made a prerequisite for publication, all species identifications could be evaluated retroactively, and our knowledge of the biology of individual species would be immune from taxonomic changes, controversy and misidentification. Adoption of this system would improve quarantine practices and the management of diseases caused by various plant pathogens.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".