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Record W1797361964 · doi:10.5376/mpb.2011.02.0001

Genetic Diversity of Involved Varieties and Improvement of Elite Restorer of Indica Rice (<em>Oryza sativa</em> L.) Using Backcross Introgression

2011· article· en· W1797361964 on OpenAlexvenueno aff
Jinteng Cui, Bingxu Chen, Yingyao Shi, Rong Zhang, Hui Wang, Yiliang Qian, Haiyan Liu, Zhikang Li, Yongming Gao

Bibliographic record

VenueMolecular Plant Breeding · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Mapping and Diversity in Plants and Animals
Canadian institutionsnot available
Fundersnot available
KeywordsIntrogressionBackcrossingOryza sativaBiologyGenetic diversityBotanyGeneticsAgronomyGenePopulation

Abstract

fetched live from OpenAlex

To make reference to cross combinations and improvement of parents, the genetic diversity and relationship among 55 rice germplasms were analyzed with a total of 53 SSR markers. In the present study, 267 allelic variations were detected, and the average allelic variation of 53 loci was 5.04, ranging from 4 to 7. The average polymorphism index content (PIC) of SSR markers was 0.624, ranging from 0.287 to 0.786. All germplasms could be divided into indica and japonica rices, the genetic similarity between them varied from 0.588 to 0.996. The similarity coefficient between Minghui 86 and 53 donors was from 0.655 to 0.850. The similarity coefficient between Shuhui 527 and the donors was from 0.640 to 0.873. The results indicated that the detection of SSR polymorphisms was not only one of the most efficient and accurate measures to study the genetic differences among rice varieties but also was helpful for the discovery and utilization of favorable genes in advanced-backcross introgression populations.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.817

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 science0.0000.001
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 head0.025
GPT teacher head0.216
Teacher spread0.191 · 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 designBench or experimental
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
Published2011
Admission routes1
Has abstractyes

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