Genetic Variability and Phylogenetic Relationship of Pakistani Snapmelon (Cucumis melo var. Momordica) by Using Microsatellite Markers
Bibliographic record
Abstract
Among the major cucurbit vegetables, Cucumis melo has one of the highest polymorphic fruit types and botanical varieties. The aim of the present study was to evaluate the genetic diversity among different genotypes of Snapmelon (Cucumis melo var. Momordica) collected from all the four provinces of Pakistan. In this study, 18 microsatellite markers were tested on Snapmelon germplasm which yielded valuable information about the genetic relationships among 40 Snapmelon accessions. The mean PIC value of the markers ranged from 0.3706 to 0.8247. For establishing data matrix, an auto radiogram was visually scored for the presence (1) or absence (0) of polymorphic bands. Assessments of genetic relationship among the genotypes were done by cluster analysis, using POPgen software. The genetic analysis through principle coordinate analysis (PCA) and dendrogram showed that the wild accessions were distinguished from all domesticated accessions collected from various regions of the country. Genetic differentiation among the populations using molecular data indicated the importance of the study area for species conservation, genetic erosion estimation, and exploitation in breeding programs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".