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Record W2109438867 · doi:10.1139/g00-081

Identification of YAC clones containing the mutable <i>slender glume</i> locus <i>slg</i> in rice (<i>Oryza sativa</i> L.)

2001· article· en· W2109438867 on OpenAlexvenueno aff
Masayoshi Teraishi, H. Hirochika, Yutaka Okumoto, Akira Horibata, H. Yamagata, Takatoshi Tanisaka

Bibliographic record

VenueGenome · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Reproductive Biology
Canadian institutionsnot available
Fundersnot available
KeywordsGlumeContigBiologyGeneticsLocus (genetics)Restriction fragment length polymorphismYeast artificial chromosomeOryza sativaGene mappingTransposable elementBackcrossingChromosomeGeneMolecular biologyGenomeBotanyGenotype

Abstract

fetched live from OpenAlex

A mutable slender glume gene slg, which often reverts to the wild-type state, was induced by gamma-ray irradiation of seeds of the japonica rice cultivar 'Gimbozu'. The final goal was to understand whether the slender glume mutation was associated with the insertion of a transposable element, utilizing map-based cloning techniques. The RFLP (restriction fragment length polymorphism) analysis revealed that the slg locus was located between two RFLP loci, XNpb33 and R1440, on chromosome 7 with recombination values of 3.1% and 1.0%, respectively. Using these two RFLP loci as probes, five YAC (yeast artificial chromosome) clones containing either of these two loci were selected from a YAC library. Subsequently, both end fragments of these YAC clones, amplified by the inverse PCR (IPCR) method, were used to select new YAC clones more closely located to the slg locus. After repeating such a procedure, we successfully constructed a 6-cM YAC contig, and identified four overlapping YAC clones, Y1774, Y3356, Y5124, and Y5762, covering the slg locus. The chromosomal location of the slg was narrowed down to the region with a physical distance of less than 280 kb between the right-end fragments of Y1774 and Y3356.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.488

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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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

Citations14
Published2001
Admission routes1
Has abstractyes

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