<i>Prunus avium</i>: nuclear DNA study in wild populations and sweet cherry cultivars
Bibliographic record
Abstract
The PCR-SSR technique was used to detect nuclear DNA diversity in five wild populations of Prunus avium from deciduous forests in Italy, Slovenia, and Croatia and 87 sweet cherry accessions from different geographical areas that have been maintained in the sweet cherry collection in Italy. This sweet cherry collection includes local accessions from the Campania Region as well as accessions from different countries. Twenty-eight microsatellites, previously developed in this species, generated polymorphic amplification products. Between 2 and 14 alleles were revealed for the polymorphic loci studied, with the expected heterozygosity ranging from 0.045 to 0.831. The total probability of identity was 56.94 x 10-18. A model-based Bayesian clustering analysis identified nine distinct gene pools in cultivated P. avium. The probability that wild populations were assigned to cultivated gene pools indicated that three gene pools accounted for the genomic origin of 53% of P. avium sampled. A dendrogram was generated using UPGMA (unweighted pair group method with arithmetic averages) based on Nei genetic distance analysis. This dendrogram classified most of the genotypes into one major group with an additional group of five accessions. The results indicate that this set of SSRs is highly informative, and they are discussed in terms of the implications for sweet cherry characterization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 teacher head, 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".