A meta-analysis of seed protein concentration QTL in soybean
Bibliographic record
Abstract
Qi, Z.-m., Sun Y.-n., Wu, Q., Liu, C.-y., Hu, G.-h. and Chen, Q.-s. 2011. A meta-analysis of seed protein concentration QTL in soybean. Can. J. Plant Sci. 91: 221–230. An integrated map of QTLs related to seed protein concentration in soybean has been constructed, based on the public genetic map, soymap2 as a reference map, along with a set of 107 QTLs reported in the literature over the past 20 yr. Each of these QTLs was projected onto the soymap2 by software package BioMercator v2.1. Twenty-three consensus QTLs were detected. The confidence interval at all sites ranged from 1.52 to 14.31cM, and the proportion of the phenotypic variance associated with each of them from 1.5 to 20.8%. Major chromosomal sites were identified on LG I (Gm20), four important sites were identified, involving LG A1 (Gm05), B2 (Gm14), E (Gm07) and M (Gm15). A meta-analysis approach was used to improve the precision of the location of these sites. These results facilitate gene mining and molecular assist-selection in soybean.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".