Genetic map of triticale compiling DArT, SSR, and AFLP markers
Bibliographic record
Abstract
A set of 90 doubled haploid (DH) lines derived from F(1) plants that originated from a cross between × Triticosecale Wittm. 'Saka3006' and ×Triticosecale Wittm. 'Modus', via wide crossing with maize, were used to create a genetic linkage map of triticale. The map has 21 linkage groups assigned to the A, B, and R genomes including 155 simple sequence repeat (SSR), 1385 diversity array technology (DArT), and 28 amplified fragment length polymorphism (AFLP) markers covering 2397 cM with a mean distance between two markers of 4.1 cM. Comparative analysis with wheat consensus maps revealed that triticale chromosomes of the A and B genomes were represented by 15 chromosomes, including combinations of 2AS.2AL#, 2AL#2BL, 6AS.6AL#, and 2BS.6AL# instead of 2A, 2B, and 6A. In respect to published maps of rye, substantial rearrangements were found also for chromosomes 1R, 2R, and 3R of the rye genome. Chromosomes 1R and 2R were truncated and the latter was linked with 3R. A nonhomogeneous distribution of markers across the triticale genome was observed with evident bias (48%) towards the rye genome. This genetic map may serve as a reference linkage map of triticale for efficient studies of structural rearrangements, gene mapping, and marker-assisted selection.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".