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Genetic diversity in soybean genotypes from north‐eastern China and identification of candidate markers associated with maturity rating

2008· article· en· W2096926759 on OpenAlexaff
Wei Li, Yingpeng Han, D. Zhang, Mei Yang, Weili Teng, Zhenfeng Jiang, Lijuan Qiu, Genlou Sun

Bibliographic record

VenuePlant Breeding · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsRAPDBiologyCultivarGenetic diversityGenetic similarityGenotypeGenetic markerHorticultureBotanyGeneticsGenePopulation

Abstract

fetched live from OpenAlex

Abstract Random amplified polymorphic DNA (RAPD) and simple sequence repeat (SSR) markers were used to estimate the genetic relationships among 101 soybean cultivars developed in north‐eastern China. Fifty‐three fragments of the 100 RAPD markers and 35 SSR markers tested were polymorphic across the 101 soybean cultivars. Similarity values among these soybean cultivars ranged from 45.2% to 100% for RAPD data, and ranged from 36.1% to 100% for SSR data. The similarity matrices for SSR data and RAPD data were moderately correlated ( r = 0.31, P < 0.05). Cluster analyses indicated that the cultivars released from the same seed company were mostly grouped together. A principal component analysis, based on the combined RAPD and SSR data, yielded a good separation of soybean varieties with different maturity ratings [represented by soybean Heat Unit (HU)]. The varieties with HU < 2200 were well separated from those with HU > 2200. Four RAPD markers and eight SSR markers were significantly associated with the maturity ratings of soybean.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.023
GPT teacher head0.178
Teacher spread0.155 · 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

Citations15
Published2008
Admission routes1
Has abstractyes

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