Microsatellite-AFLP for genetic mapping of complex polyploids
Bibliographic record
Abstract
In spite of the economical relevance of polyploid crops, genetic mapping of these species has been relatively overlooked. This is because of intrinsic difficulties such as the uncertainty of the chromosome behavior at meiosis I and the need for very large segregating populations. An important, yet underestimated issue, in mapping polyploids is the choice of the molecular marker system. An ideal molecular marker system for polyploid mapping should maximize the percentage of single dose markers (SDMs) detected and the possibility of recognizing allelic markers. In the present work, the marker index for genetic mapping (MIgm) of M-AFLP is compared with that of AFLP and SAMPL. M-AFLPs have the highest MIgm values (22 vs. 18.5 of SAMPL and 9.83 of AFLP) mostly because of their high power to detect polymorphism. Owing to their prevalent codominant inheritance, it is proposed that M-AFLP can be used for the preliminary identification of hom(e)ologous groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".