Screening of<i>Brassica napus</i>against blackleg caused by<i>Leptosphaeria maculans</i>: effects of inoculum concentration, subculturing of the pathogen, and time of disease screening
Bibliographic record
Abstract
The effects of inoculum concentration, subculturing of the pathogen, and time of disease screening on the development of blackleg disease caused by Leptosphaeria maculans were studied using the Brassica napus canola cultivars Quantum (resistant) and Profit (susceptible). Disease development was not affected by inoculum concentration in the range of 5 × 105 - 4 × 106 pycnidiospores/mL or subculturing of stock cultures of L. maculans up to 71 times on V8 juice rose Bengal agar. Disease development, however, showed seasonal variation in the greenhouse. While the disease severity values for the resistant cultivar Quantum increased during the summer, those for the susceptible cultivar Profit remained consistent throughout the year.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".