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Record W4395098289 · doi:10.5376/rgg.2024.15.0004

Genetic Regulation of Diurnal Flowering Time Divergence in Rice: The Role of the OsMYB8 and OsJAR1 Module

2024· article· en· W4395098289 on OpenAlexvenueno aff
zhong jianli, Fang Jim

Bibliographic record

VenueRice Genomics and Genetics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Mapping and Diversity in Plants and Animals
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsDivergence (linguistics)Genetic divergenceBiologyDiurnal temperature variationGeographyMeteorologySociologyGenetic diversityDemography

Abstract

fetched live from OpenAlex

On March 13, 2024, a joint research achievement by the State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, School of Life Sciences, South China Agricultural University, the Guangdong Provincial Key Laboratory of New Technology in Rice Breeding, Rice Research Institute of Guangdong Academy of Agricultural Sciences, and the Life Sciences Technology Center of China National Seed Group Co., Ltd. was published in Nature Communications. The paper, titled "Natural variation in OsMYB8 confers diurnal floret opening time divergence between indica and japonica subspecies," had Yajun Gou and Yueqing Heng as co-first authors, with Rongxin Shen and Haiyang Wang as co-corresponding authors. The study was funded by the National Natural Science Foundation of China Innovation Group Project and the Hainan Yazhou Bay Seed Laboratory Commander Project, among others. It identified the OsMYB8 gene as a key factor regulating the divergence in diurnal flowering time in rice. The interaction between OsMYB8 and OsJAR1 significantly affects the flowering time of indica and japonica rice. Transferring the indica allele of OsMYB8 into japonica rice effectively advances flowering time, providing a new strategy for indica-japonica hybrid breeding.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score0.262

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 head0.004
GPT teacher head0.187
Teacher spread0.183 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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