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Record W2985891560 · doi:10.5539/jmbr.v9n1p149

Genetic Basis of Giant Embryo Traits and Effects of Environmental Factors on Giant Embryo Rice

2019· article· en· W2985891560 on OpenAlexvenueno aff
Bo Peng, Kun Xu, Kun He, Dongying Tang, Juan Peng, Xia-Yu Tian, Yanfang Sun, Xiaohua Song, Lulu He, Rui-Hua Pang, Jintao Li, Quanxiu Wang, Wei Zhou, Huilong Li, Hongyu Yuan, A Xinxiang

Bibliographic record

VenueJournal of Molecular Biology Research · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGABA and Rice Research
Canadian institutionsnot available
FundersNanhu Scholars Program for Young Scholars of Xinyang Normal UniversityXinyang Normal UniversityNational Natural Science Foundation of China
KeywordsEmbryoBiologyBiotechnologyGenetics

Abstract

fetched live from OpenAlex

Giant embryo rice (GMR) is a special rice which can produce eutrophic functional rice. Giant embryo rice and its intensive processing products have been widely used in food, medicine, health care products and other fields, with extremely important scientific significance and economic value. In recent years, a series of important advances have been made in the research of giant embryo rice, and its achievements have attracted the attention of rice breeders and consumers at home and abroad. In this paper, the genetic basis of giant embryo traits and the effects of environmental factors on giant embryo rice were reviewed and analyzed, and the application prospect of giant embryo rice was also prospected, these will provide important reference for genetic improvement and application promotion of giant embryo rice.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.019
GPT teacher head0.286
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), 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
Published2019
Admission routes1
Has abstractyes

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