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Record W2943744513

Identification of QTL for ratooning ability and grain yield traits in ratoon rice based on SSR marker

2004· article· en· W2943744513 on OpenAlexvenueno aff
Jingsheng Zheng, Yizhen Li, Wenxiong Lin

Bibliographic record

Venue分子植物育种 · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGABA and Rice Research
Canadian institutionsnot available
Fundersnot available
KeywordsRatooningPanicleQuantitative trait locusBiologyAgronomyCultivarGrain yieldYield (engineering)PopulationCrop yieldGeneGeneticsMedicine
DOInot available

Abstract

fetched live from OpenAlex

An F_(2) population and its corresponding SSR marker linkage map were established and constructed from a cross between two indica rice cultivars, Minghui86 and Jiafuzhan. QTL for ratooning ability and grain yield traits in ratoon rice was identified and analyzed. The results showed that 1 QTL for ratooning ability (panicle per plant), 1 QTL for grain yield and 2 QTL for spikelet per panicle and seed-setting were detected. Their additive effects were from Minghui 86 with same direction effects and increasing effects. QTL conferring ratooning ability (panicle per plant), seed-setting and grain yield of ratoon rice were located in same linked regions of chromosome 7. This explained very well that the very significantly positive correlationship exists between ratooning ability and grain yield or seed-setting.

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)0.001
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 score0.967
Threshold uncertainty score0.095

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.034
GPT teacher head0.273
Teacher spread0.239 · 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

Citations4
Published2004
Admission routes1
Has abstractyes

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