Quantitative trait locus analysis of multiple agronomic traits in the model legume<i>Lotus japonicus</i>
Bibliographic record
Abstract
The first quantitative trait locus (QTL) analysis of multiple agronomic traits in the model legume Lotus japonicus was performed with a population of recombinant inbred lines derived from Miyakojima MG-20 x Gifu B-129. Thirteen agronomic traits were evaluated in 2004 and 2005: traits of vegetative parts (plant height, stem thickness, leaf length, leaf width, plant regrowth, plant shape, and stem color), flowering traits (flowering time and degree), and pod and seed traits (pod length, pod width, seeds per pod, and seed mass). A total of 40 QTLs were detected that explained 5%-69% of total variation. The QTL that explained the most variation was that for stem color, which was detected in the same region of chromosome 2 in both years. Some QTLs were colocated, especially those for pod and seed traits. Seed mass QTLs were located at 5 locations that mapped to the corresponding genomic positions of equivalent QTLs in soybean, pea, chickpea, and mung bean. This study provides fundamental information for breeding of agronomically important legume crops.
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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) | 0.000 | 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".