<i>Plasmodiophora brassicae</i> in Mexico, from anecdote to fact
Bibliographic record
Abstract
ABSTRACT For years, the presence of clubroot disease and its causal agent, Plasmodiophora brassicae , in Mexico has been given by granted. However, after a long search in the scientific literature in English and Spanish, as well as grey literature including thesis and government reports, we were not able to find any information regarding the actual detection of the pathogen, hosts affected, areas with the disease, or any real information about clubroot (‘hernia de la col’, in Mexico). To confirm if P. brassicae was indeed in Mexico, we started a true detective adventure. First, we identified agricultural communities in south-east Mexico known to grow cruciferous crops. Second, we asked to the growers if they have ever seen clubroot symptoms, showing them during the inquires pictures of the characteristic galls that might have been present in their crops. Third, we collected soil from two of the communities with positive response and grew an array of cruciferous in the soil as baits to “fish” the clubroot pathogen. We detected the presence of galls in the roots of 32 plants and observed the presence of resting spores. Through a P. brassicae specific PCR assay, we were able to confirm the presence of the clubroot pathogen in the samples and in Mexico for the very first time. This study is the first report and identification of P. brassicae in Mexico, opening the doors to understand the genetic diversity of this elusive and devastating plant 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 | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".