Rapid classification of partial waxy wheats using PCR-based markers
Bibliographic record
Abstract
Mutations in the three homeologous waxy loci Wx-A1, Wx-B1, and Wx-D1 of a waxy wheat line have previously been characterized at the molecular level. Using combinations of these mutations, six types of partial waxy wheat plus wild type and waxy wheat (types 1-8) can be produced. Here, we describe primer sets for all three loci that can be used under a single set of conditions, allowing 32 lines to be characterized as types 1-8 in a single PCR run using a 96-well plate. Using multiplex PCR, mutations at the Wx-B1 and Wx-D1 loci can be identified in a single PCR, reducing the number of reactions necessary to identify and select the desired partial waxy wheat line. A single multiplex PCR can be used to detect all three mutations when products are analyzed using capillary electrophoresis on a microchip device. The PCR conditions and primers are effective with a number of cultivars from other countries, indicating that the mutations found at the Wx-A1 and Wx-B1 loci of these cultivars likely have the same origins as the mutations in the corresponding loci of the waxy wheat line used in this study. The PCR selection method described here is an easy and effective alternative to the commonly used SDS-PAGE methods for identification of null alleles.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".