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Record W2092353808 · doi:10.1139/g04-016

Ancestral genome duplication in rice

2004· article· en· W2092353808 on OpenAlexvenueno aff
Romain Guyot, Beat Keller

Bibliographic record

VenueGenome · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsnot available
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsGenomeBiologyGene duplicationGenome evolutionSegmental duplicationGeneticsGenome sizeEvolutionary biologyOryzaStructural variationGeneOryza sativaGene family

Abstract

fetched live from OpenAlex

The recent availability of the pseudochromosome sequences of rice allows for the first time the investigation of the extent of intra-genomic duplications on a large scale in this agronomically important species. Using a dot-matrix plotter as a tool to display pairwise comparisons of ordered predicted coding sequences along rice pseudochromosomes, we found that the rice genome contains extensive chromosomal duplications accounting for 53% of the available sequences. The size of duplicated blocks is considerably larger than previously reported. In the rice genome, a duplicated block size of >1 Mb appears to be the rule and not the exception. Comparative mapping has shown high genetic colinearity among chromosomes of cereals, promoting rice as a model for studying grass genomes. Further comparative genome analysis should allow the study of the conservation and evolution of these duplication events in other important cereals such as rye, barley, and wheat.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.021
GPT teacher head0.220
Teacher spread0.199 · 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 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

Citations176
Published2004
Admission routes1
Has abstractyes

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