Genetic and molecular analysis of fasciation mutation in Japanese soybeans
Bibliographic record
Abstract
Soybean fasciation is controlled by a recessive gene affecting the shape of the aerial parts of the plant, which is characterized by flattened stem, infrequent branches and clustering of flowers and pods on shoot apices. Morphological feature of the fasciation mutation has been dissected, but molecular information is still limited. We developed three populations derived from the crosses between wild type cultivars and three Japanese fasciation varieties, Shakujodaizu, Taikadaizu and Shakujomame, respectively. The molecular mapping of the three F2 populations revealed that the fasciation locus (F locus) was mapped on the chromosome 2 (LG D1b). Fine mapping experiment with a population consisting of 1536 seeds derived from the F2 lines segregating for fasciation revealed that a DNA marker cosegregated with the fasciation phenotype. This DNA marker was dominant for wild type allele and the flanking region of this marker could not be amplified in Shakujodaizu as well as in the other two fasciation varieties, suggesting that some deletion or major rearrangement probably occurred at the f allele. Genomic information disclosed two predicted genes, Glyma02g36940 and Glyma02g36960, that were annotated in the vicinity of this DNA marker. The relationship between these candidate genes and the fasciation phenotype was discussed.
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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 | 0.000 | 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) | 0.001 | 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".