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Record W3151417802

小麦花器官形成的A,B,C,D,E功能基因研究进展

2016· article· zh· W3151417802 on OpenAlexvenueno aff
魏淑红, 廖明莉

Bibliographic record

Venue分子植物育种 · 2016
Typearticle
Languagezh
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science
DOInot available

Abstract

fetched live from OpenAlex

小麦是人类重要的粮食作物之一,花器官是粮食产生的基础。小麦花器官发育研究对小麦育种有着潜在的应用前景。目前,已鉴定克隆了部分小麦花器官A,B,C,D,E 5类功能基因,加深了人们对小麦花器官发育机制的认识。A功能基因主要有WFUL1,2,3/WAP1/VRN1/TaVRT1/TaAP1-1,2,3,与小麦由营养生长向生殖生长转变以及内外稃和浆片的发育有关。B功能基因有WAP3/TaAP3/TaMADS 51、TaMADS 82、WPI1/TaPI-1、WPI2/TaPI-2/TaAGL26,决定浆片和雄蕊的发育。C功能基因参与雄蕊和雌蕊的发育,包括WAG-1/TaAG-1、WAG-2/TaAG-2/WM29A/WM29B/TaAGL39。D功能基因在胚珠发育中起重要作用,主要有TaAG-3/TaAGL2/TaAGL9/TaAGL31、TaAG-4和WSTK。E功能基因在各轮花器官中均有一定作用,主要有WSEP、WLHS1、TaMADS1、TaSEP-1,2,3,4,5,6,以及TaAGL37/TaAGL6-1A,TaMADS#12/TaAGL6-1B和TaAGL6-1C。相比于双子叶植物,小麦花器官发育仍有许多问题尚需阐明。本文综述了小麦花器官形成的A,B,C,D,E功能基因研究现状,总结小麦花器官形成的ABCDE模型,并提出目前研究存在的问题,为深入研究小麦花器官发育提供一定的理论依据。

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.997

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)0.0040.004

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 head0.027
GPT teacher head0.228
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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