The use of multiple alien chromosome addition aneuploids facilitates genetic linkage mapping of the<i>Gossypium</i>G genome
Bibliographic record
Abstract
Primary germplasm pools represent the most accessible source of new alleles for crop improvement, but not all effective alleles are available in the primary germplasm pool, and breeders must sometimes confront the difficulties of introgressing genes from the secondary and tertiary germplasm pools in cotton by using synthetic polyploids as introgression bridges. Two parental Gossypium nelsonii x Gossypium australe AFLP genetic linkage maps were used to identify G genome chromosome-specific molecular markers, which in turn were used to track the fidelity and frequency of G. australe chromosome transmission in a Gossypium hirsutum x G. australe hexaploid bridging family. Conversely, when homoeologous recombination is low, first generation aneuploids are useful adjuncts to genetic linkage mapping. Although locus ordering was not possible, the distribution of AFLP markers among 18 multiple chromosome addition aneuploids identified mapping errors among the G. australe and G. nelsonii linkage groups and assigned non-segregating G. australe AFLPs to linkage groups. Four putatively recombined G. australe chromosomes were identified in 5 of the 18 aneuploids. The G. australe and G. nelsonii genetic linkage maps presented here represent the first AFLP genetic linkage maps for the Gossypium G genome.
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".