Multivariate analysis of apple cultivar susceptibility to<i>Venturia inaequalis</i>under greenhouse conditions
Bibliographic record
Abstract
Apple scab, caused by Venturia inaequalis, is a disease of great importance in apple production regions in eastern North America. However, little is known regarding the relative susceptibility of North American cultivars to this disease since the majority of previous researches on apple scab were conducted on a highly susceptible cultivar, 'McIntosh'. We evaluated 21 cultivars commonly grown in eastern and central Canada for their responses to V. inaequalis by measuring the following components of partial resistance: the number of lesions per leaf, the number of lesions per square centimetre of leaf, the lesion surface area per leaf, the proportion of leaf area diseased, the number of conidia per lesion, the number of conidia per square centimetre of lesion, the incubation period, and the latent period. All of the components examined were effective in assessing relative cultivar susceptibility, but those related to disease severity, latent period, and conidia production were the most important and accounted for 86% of the variation among cultivars. Numbers of lesions per leaf and per square centimetre of leaf were highly positively correlated with principal component 1 (PC1). Incubation and latent periods were highly negatively correlated with PC1. 'McIntosh' and 'Vista Bella' were found to be highly susceptible whereas 'Golden Russet', 'Idared', 'Paulared', 'Red Delicious', and 'Sunrise' were the least susceptible.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".