SSR cross-amplification and variation within coffee trees (<i>Coffea</i>spp.)
Bibliographic record
Abstract
Primer sets were developed from 85 Coffea arabica sequences in addition to 25 already published primer sets. They were subsequently used for amplification in six African Coffea species: Coffea canephora (CAN), Coffea eugenioides (EUG), Coffea heterocalyx (HET), Coffea liberica (LIB), Coffea sp. Moloundou (MOL) and Coffea pseudozanguebariae (PSE). The amplification percentages for these 110 primer pairs ranged from 72.7% for LIB to 86.4% for PSE. Good transferability was thus obtained within the Coffea genus. When focusing on the two species CAN and PSE, high genetic diversity, high polymorphic locus rates (above 80%) and a mean allele number per polymorphic locus of more than 3 were noted. The estimated null allele percentage was -11% for PSE and -9% for CAN. Sixty three percent (CAN) and 79.5% (PSE) of the fixation index (Fis) values were positive. The within-species polymorphism information content (PIC) distribution showed two modes for both species. Although the two species shared 30 polymorphic loci, no correlation between CAN and PSE PIC values was obtained. All of these data are discussed in relation to the polymorphism level and the potential use of these SSRs for subsequent analysis of genetic diversity or genetic mapping.
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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) | 0.001 | 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) | 0.002 | 0.001 |
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".