Assessing the genetic relationships of Curcuma alismatifolia varieties using simple sequence repeat markers
Bibliographic record
Abstract
The genus Curcuma is a member of the ginger family (Zingiberaceae) that has recently become popular for use as flowering pot plants, both indoors and as patio and landscape plants. We used PCR-based molecular markers (SSRs) to elucidate genetic variation and relationships between five varieties of Curcuma (Curcuma alismatifolia) cultivated in Malaysia. Of the primers tested, 8 (of 17) SSR primers were selected for their reproducibility and high rates of polymorphism. The number of presumed alleles revealed by the SSR analysis ranged from two to six alleles, with a mean value of 3.25 alleles per locus. The values of HO and HE ranged from 0 to 0.8 (mean value of 0.2) and 0.1837 to 0.7755 (mean value of 0.5102), respectively. Eight SSR primers yielded 26 total amplified fragments and revealed high rates of polymorphism among the varieties studied. The polymorphic information content varied from 0.26 to 0.73. Dice's similarity coefficient was calculated for all pairwise comparisons and used to construct an unweighted pair group method with arithmetic average (UPGMA) dendrogram. Similarity coefficient values from 0.2105 to 0.6667 (with an average of 0.4386) were found among the five varieties examined. A cluster analysis of data using a UPGMA algorithm divided the five varieties/hybrids into 2 groups.
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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) | 0.000 | 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) | 0.000 | 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 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".