Evaluation of Soybean Varieties in the Northern Uniform Soybean Test—Uniform Test I
Bibliographic record
Abstract
The Northern Uniform Soybean Test is used to evaluate soybean varieties produced by several public breeding programs in the northern portion of the United States and Canada. In 2010, five public breeding programs participated in the Northern Uniform Soybean Test (Uniform Test I). Public breeders are allowed to enter varieties into the Uniform Test in exchange for growing locations for the test. Material entered into the Uniform Test is generally in advanced stages of a breeding program. The Uniform Soybean Test is an efficient method for soybean breeders to get multiple location data, in a very efficient manner in comparison to each individual program growing their own locations. It also produces useful information by comparing soybean lines from multiple programs, and identifies lines from other states that produce well in northern Iowa. Results from these tests are used by breeders to select varieties with superior yield and/or disease resistance to continue advancement on a trek toward variety release. These results are also used to demonstrate positive characteristics to growers and other interested parties.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".