Registration of ‘MSU E5024’ Wheat
Bibliographic record
Abstract
‘MSU E5024’ (Reg. No. CV‐1077, PI 664078) soft white winter wheat ( Triticum aestivum L.) was developed by Michigan State University (MSU) AgBioResearch and released in 2011 via exclusive licensing agreements through MSU Technologies. In addition to researchers at MSU, USDA‐ARS researchers at the Soft Wheat Quality Laboratory (Wooster, OH) conducted quality evaluations during the development of MSU E5024. Deoxynivalenol testing was performed at the University of Minnesota, and molecular marker analyses were performed at the USDA‐ARS Regional Small Grains Genotyping Laboratory (Raleigh, NC). The objective of the cross was to create a high‐yielding soft white winter wheat cultivar adapted to Michigan and the surrounding region with good agronomic performance, acceptable quality, and good disease resistance. Soft white winter wheat is used in many wheat‐related industries and is a large portion of the wheat market in Michigan. MSU E5024 (experimental number E5024) is an F 7 –derived line developed using pedigree breeding. MSU E5024 exhibits a stable and high level of performance, including good yield, high test weight, resistance to powdery mildew [caused by Blumeria graminis (DC.) E.O. Speer], and improved resistance to Fusarium head blight (caused by Fusarium graminearum Schwabe) and preharvest sprouting. MSU E5024 is short, white chaffed, and awned. MSU E5024 is well adapted to Michigan and to Ontario, Canada).
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.020 |
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".