Genome-wide association study of dynamic developmental plant height in soybean
Bibliographic record
Abstract
Plant height (PH) is an important agronomic trait affecting crop yield and quality. In this study, a soybean collection of 192 natural accessions and 1536 single nucleotide polymorphism (SNP) makers were used to identify genomic regions associated with PH. There is a large genetic variation in PH with a diverse panel. Three phenotypic indexes (PH measured at six stages, the conditional PH, and the relative growth rates of PH) were used to identify developmental behavior for PH in soybean. Six methods were used to minimize false-positive associations in association mapping, and finally the generalized linear model for principal component analysis had been used in this study. Three SNPs, BARC-040651-07807, BARC-030433-06867, and BARC-042475-08274, were highly significantly associated with PH in the final growing period, and two SNPs, BARC-038795-07333 and BARC-013749-01246, were connected with PH in the early growing period.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".