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Record W4394772609 · doi:10.5376/bm.2024.15.0001

Rapid Detection of Rice Fragrance Allele <i>badh2-E7</i> by Recombinant Polymerase Amplification (RPA)

2024· article· en· W4394772609 on OpenAlexvenueno aff
Jihua Zhou, Anpeng Zhang, Wenke Xu, Can Cheng, Fuan Niu, Bin Sun, Liming Cao, Jianming Zhang, Huangwei Chu

Bibliographic record

VenueBioscience Methods · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGABA and Rice Research
Canadian institutionsnot available
Fundersnot available
KeywordsGenotypingMolecular biologyBiologyVariants of PCRPolymerase chain reactionAlleleGeneBetaineMarker-assisted selectionRecombinant DNAGeneticsGenetic markerGenotypeBiochemistry

Abstract

fetched live from OpenAlex

Fragrant rice is favored deeply by consumers due to the strong fragrance. Fragrant rice is mainly caused by the loss-of-function mutation of the Betaine aldehyde dehydrogenase 2 ( Badh2 ) gene in rice. Badh2-E7 , with 8 bp deletion and 3 bp substitution in exon 7 of Badh2 , is the main mutation allele used in fragrant rice breeding. In this study, a genotyping method named RPA-badh2-E7 for Badh2-E7 allele was designed. This method has the characteristics of rapid (completed amplification in 5 min), sensitivity (100-fold than conventional PCR), no strict amplification conditions required (25 °C~45 °C), and independent of PCR amplifier (only one thermostatic incubator is enough for amplification). This method greatly improved the efficiency of molecular marker-assisted selection of rice fragrant genes and breeding of fragrant rice varieties.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.005

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 head0.040
GPT teacher head0.328
Teacher spread0.288 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2024
Admission routes1
Has abstractyes

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