BELAROSA - Mise au point d’un test en routine d’identification de la sensibilité/résistance à la maladie des taches noires de variétés de rosier en vue de leur commercialisation.
Bibliographic record
Abstract
The fungus Diplocarpon rosaeis the causal agent of black spot disease on rose, a widespread and devastating disease in the outdoor landscape. In this study, a collection of 77 monoconidial fungal strains collected on cultivated roses(50 strains from Europe and Asia) and wild roses (27 strains from Kazakhstan) was established.Twostrains of D. rosaewere sequenced by using Illumina® technology. Based on nucleotide polymorphism of the two fungal strains, 27 polymorphic microsatellite markers were identified. Polymorphism analysis of the 77 strains revealed a strong genetic differentiation between strains from cultivated roses and those from wild roses. A pathogenicity assay in controlled conditions (greenhouse) was developed using 10 French fungal strains and 19 rose cultivars. Using this assay, new rose cultivars were evaluated for their resistance against these 10 fungal strains. Good correlation observed between resistance scoring in greenhouse conditions and in field indicates that pathogenicity assays in controlled conditions could be very useful in the near future to rapidly characterise the resistance of new rose varieties to black spot disease
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".