High-throughput Identification and Marker Development of Perfect SSR for Cultivated Genus of Passion Fruit (<i>Passiflora edulis</i>)
Why this work is in the frame
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Bibliographic record
Abstract
Simple sequence repeat (SSR) markers are characterized by high polymorphism, good reproducibility and co-dominance etc. They can be easily applied to develop efficient, simple and practical molecular markers. In the present study, bioinformatics methods were applied to identify high-throughput perfect SSRs of cultivar Passiflora genome. A total of 13,104 perfect SSRs were obtained. SSR core sequence structure is mainly 2-4 bases, the maximum numbers are TA, AT, TC and AG. The maximum numbers of repetitions were up to 20 times. A total of 12,934 pairs of SSR markers were developed by using bioinformatics software, and 20 pairs of markers were selected for amplification specificity assessment of MTX and WJ10, and the polymorphism rate was as high as 60%. The large-scale development of the SSR markers of Passiflora cultivar has paved a foundation for the efficient utilization of the germplasm resources of passion fruit, genetic improvement of the varieties and molecular breeding.
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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 it