Development, characterisation, and across-taxa utility of oil palm (<i>Elaeis guineensis</i> Jacq.) microsatellite markers
Bibliographic record
Abstract
The results of the development of oil palm (Elaeis guineensis Jacq.) microsatellite markers are given step by step, from the screening of libraries enriched in (GA) n , (GT) n , and (CCG) n simple-sequence repeats (SSRs) to the final characterisation of 21 SSR loci. Also published are primer sequences, estimates of allele size range, and expected heterozygosity in E. guineensis and in the closely related species E. oleifera, in which an optimal utility of the SSR markers was observed. Multivariate data analyses showed the ability of SSR markers to efficiently reveal the genetic-diversity structure of the genus Elaeis in accordance with known geographical origins and with measured genetic relationships based on previous molecular studies. High levels of allelic variability indicated that E. guineensis SSRs will be a powerful tool for genetic studies of the genus Elaeis, including variety identification and intra- or inter-specific genetic mapping. PCR amplification tests on a subset of 16 other palm species and allele-sequence data showed that E. guineensis SSRs are putative transferable markers across palm taxa. In addition, phenetic information based on SSR flanking region sequences makes E. guineensis SSR markers a potentially useful molecular resource for any researcher studying the phylogeny of palm taxa.Key words: Palmae, SSR, phenetic analysis, phylogeny.
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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 | 0.001 | 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) | 0.002 | 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".