GrainGenes: Tools and Content to Assist Breeders Improving Oat Quality
Bibliographic record
Abstract
GrainGenes is the USDA-ARS database and Web resource for wheat, barley, oat, rye, and their relatives. As a community Web hub and database for small grains, GrainGenes strives to provide resources for researchers, students, and plant breeders to improve traits such as quality, yield, and disease resistance. Quantitative trait loci (QTL), genes, and genetic maps for quality attributes in GrainGenes represent the historical approach to mapping genes for groat percentage, test weight, protein, fat, and β-glucan content in oat (Avena spp.). Genetic maps are viewable in CMap, the comparative mapping tool that enables researchers to take advantage of highly populated consensus maps to increase the marker density around their genes-of-interest. GrainGenes hosts over 50 genome browsers and is launching an effort for community curation, including the manually curated tracks with beta-glucan QTL and significant markers found via GWAS and cloned cellulose synthase-like AsClF6 alleles.
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 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 | 0.000 | 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 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".