Characterization of the Non-Darkening Gene in a Cranberry Bean (Phaseolus vulgaris L.) Background
Bibliographic record
Abstract
Several common bean (Phaseolus vulgaris L.) market classes, including cranberry bean, demonstrate seed coat post-harvest darkening (PHD). PHD is associated with poor quality, lowering the overall value of the bean. A candidate MYB was sequenced in darkening (RD) and non-darkening (ND) cranberry bean lines to determine any differences between them. The RD and ND lines were identical for the candidate MYB. An F2 population of a cross between Etna (RD) and Witrood (ND) was created to study the inheritance of the PHD trait and identify its genomic location. The F2 lines were genotyped using Single Nucleotide Polymorphism (SNP) markers and used to develop a linkage map with 11 linkage groups. Multiple QTL Mapping (MQM) identified two QTL associated with colour parameter values on chromosome 10. SNP markers identified with the ND loci may be used in the future for marker assisted selection to develop ND cultivars.
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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".