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Evaluation of Soybean Varieties in the Northern Uniform Soybean Test

2010· report· en· W353575437 on OpenAlexaboutno aff
S. R. Cianzio, Peter Lundeen, Kyle Vander Molen, Gregory D. Gebhart

Bibliographic record

Venuenot available
Typereport
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsnot available
FundersIowa Soybean Association
KeywordsBiologyAgronomy

Abstract

fetched live from OpenAlex

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 2009, five public breeding programs participated in the Northern Uniform Soybean Test (Maturity Group I). Public breeders are allowed to enter varieties in the Uniform Test in exchange for growing locations for the test. Material entered in the Uniform Test is generally from advanced stages of a breeding program. The Uniform Soybean Test is an efficient method for soybean breeders to get multiple location data 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 to variety release. These results are also used to demonstrate positive characteristics to growers and other interested parties.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.068
GPT teacher head0.280
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2010
Admission routes1
Has abstractyes

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