Genetic Diversity of <i>Ascochyta rabiei</i> in Canada
Bibliographic record
Abstract
Assessment of variability of Ascochyta rabiei (teleomorph: Didymella rabiei) was based on virulence tests of 40 isolates and on random amplified polymorphic DNA (RAPD) analysis of 39 isolates from Canada. In addition, isolates of A. rabiei from other countries were assessed in the virulence (18 isolates) and RAPD (20 isolates) analyses. Seven isolates of A. lentis (teleo-morph: Didymella lentis) and two of A. pinodes (teleomorph: Mycosphaerella pinodes) also were included in the RAPD analysis. Significant line-isolate interactions in the virulence tests indicated that certain isolates were virulent only on certain lines. Canadian isolates were grouped into 14 pathotypes using eight chickpea differentials. These groupings also encompassed 17 of the 18 isolates from other countries. RAPD analysis of all 68 isolates using 8 primers produced 112 fragments, of which 96% were polymorphic. Similarities among A. rabiei isolates from Canada ranged from 20 to 100%. In the RAPD dendrogram, all five A. rabiei isolates from Australia, three of six from Syria, three of five from the United States, and one of two from India clustered within the major groups of Canadian isolates. There was a weak association between RAPD and pathotype groups. A. rabiei was 45% similar to A. lentis and only 14% similar to A. pinodes. The levels of DNA variability and virulence among isolates show that the population of A. rabiei in Canada is highly diverse.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".