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Record W2358554343

Genetic Behavior of Purple-leaf Characteristics of Rice CMS Line Xianhong A and It's Application Prospect

2010· article· en· W2358554343 on OpenAlexvenueno aff
Gao LiJun

Bibliographic record

VenueSeed · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsnot available
Fundersnot available
KeywordsJaponicaHeterosisBiologySeedlingHybridHorticultureBotany
DOInot available

Abstract

fetched live from OpenAlex

In order to study the genetic behavior of the purple-leaf characteristics,a new purple-leaf marker rice CMS line Xianhong A(B) was crossed and backcrossed with different types of indica and japonica lines with normal green leaves.The results showed that the purple leaf color of Xianhong A(B) was controlled by one pair of purple genes,and there were 1 to 2 pair of inhibitory genes could regulate the purple genes expres-sion in normal green color lines.The purple leaf color characteristics of Xianhong A(B) and the green leaf col-or characteristics of F1 combinations were stable in different environment and cultivation conditions.The pur-ple-leaf characteristics of Xianhong A was the best available seedling marker for hybrid rice seed purity identi-fication and anti-contamination and purity preserving in production.Among the hybrids derived from Xianhong A,both good plant type and strong heterosis combinations in grain yield all could be selected,and xianhong A had good application prospect in rice seed production.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.201

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)0.0000.000

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 head0.007
GPT teacher head0.209
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; a candidate call from one teacher head, 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

Citations0
Published2010
Admission routes1
Has abstractyes

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