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Record W2202045858 · doi:10.5376/pgt.2015.06.0006

Identification and Genetic Characterization of a New d10 Mutated <i>Indica</i> Rice Germplasm

2015· article· en· W2202045858 on OpenAlexvenueno aff
Zheng Jingsheng

Bibliographic record

VenuePlant Gene and Trait · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsnot available
Fundersnot available
KeywordsDwarfingGermplasmBiologyLocus (genetics)GeneGeneticsMutantTiller (botany)Genetic analysisDwarfismBotany

Abstract

fetched live from OpenAlex

Plant architecture is a determining factor for yield of cereal crop rice. Multi-tiller and dwarf mutants are useful germplasms for the study of rice plant architecture. In this research, we investigated a new multi-tiller and dwarf mutant, Jiahecong’ai (JHCA), and compared its genetic characteristics with 6 other rice varieties or lines. Two F 2 populations were developed by crossing JHCA with Gaoliangdao 1 (GLD1) and Guangchang 13 (GC13), which were used for further studies. Our results showed that the extreme dwarf and multitiller phenotype of JHCA was controlled by a recessive locus named xmd(t) . The xmd(t) locus was fine mapped to an interval between XMd-SSR4 and XMd-SSR25 marker on chromosome 2, which spans 190 kb in length including 28 annotated genes. Allelic sequence analysis revealed that the xmd(t) of JHCA has a 40-bp deletion in D10 gene, which encodes a carotenoid cleavage dioxygenase 8 (OsCCD8) involved in strigolactone (SL) biosynthesis pathway. Further genetic analysis suggested that JHCA should be a good rice germplasm for studying plant architecture in rice as well as metabolism interactions between gibberellin and strigolactone based on the reinforcement of dwarfing effect by d10 and sd1 .

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.200
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 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
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
Published2015
Admission routes1
Has abstractyes

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