<i>Plasmodiophora brassicae</i> in Mexico: From Anecdote to Fact
Bibliographic record
Abstract
For years, the presence of clubroot disease and its causal agent, Plasmodiophora brassicae, in Mexico has been stated as a fact. However, an intensive search of the scientific literature in English and Spanish, as well as gray literature including theses and government reports, did not reveal any information about the actual detection of the pathogen, affected hosts, or areas with clubroot presence, or any information about clubroot (hernia de la col in Mexico). We followed a multistep process to confirm whether P. brassicae was indeed in Mexico. First, we identified agricultural communities with a history of cruciferous crop cultivation. Second, we asked growers if they had seen clubroot on their crops, using pictures of the characteristic root galls. Third, we collected soil from the locations where clubroot was reported and looked for clubroot/P. brassicae in the soil using several cruciferous bait plants. For the first time we confirm the presence of the clubroot pathogen P. brassicae in Mexico, through a bioassay, the presence of resting spores, and a P. brassicae-specific PCR assay. The identification of P. brassicae in Mexico will contribute to our understanding of the genetic diversity of this elusive and devastating plant pathogen in future studies. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
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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 | 0.002 |
| 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 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".