Development of race-specific molecular marker for <i>Xanthomonas campestris</i> pv. <i>campestris</i> race 3, the causal agent of black rot of crucifers
Bibliographic record
Abstract
Race-specific molecular markers were established to distinguish Xanthomonas campestris pv. campestris (Xcc) race 3, the causal agent of black rot disease of crucifers. The available genome sequences of Xcc races were aligned and identified three DNA fragments specific to Xcc race 3. The identified race-specific DNA fragments namely XccR3-49, XccR3-52, and XccR3-55 were used for designing the race-specific primers to detect and identify Xcc race 3. The specificity of race-specific primers was tested against the genomic DNA extracted from Xcc (races 1–7), Xcc strains, Xc pathovars, and other bacterial species. XccR3-49, a specific sequence characterized amplified region (SCAR) primer set, gave a single band with 867 bp length for Xcc race 3 only. The remaining two markers XccR3-52 and XccR3-55 showed polymorphic amplification with amplicon sizes of 1889 and 2109 bp for Xcc race 3, respectively. Additionally, the SCAR primer set detected Xcc race 3 rapidly and efficiently in artificially infected cabbage leaves with bio-PCR. This result showed that the newly developed race-specific markers can successfully and efficiently detect and identify Xcc race 3 from Xanthomonas campestris pv. campestris races, Xanthomonas species/pathovars, as well as other plant pathogenic bacteria (Pseudomonas syringae pv. maculicola and Erwinia carotovora subsp. carotovora). Up to now, this is the first report describing the race-specific marker for the detection of Xcc race 3.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".