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Record W1979928312 · doi:10.1139/g08-120

Development of SCAR markers for sex determination in the dioecious shrub <i>Aucuba japonica</i> (Cornaceae)

2009· article· en· W1979928312 on OpenAlexvenueno aff
Masayuki Maki

Bibliographic record

VenueGenome · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyShrubBotanyGeneticsEvolutionary biology

Abstract

fetched live from OpenAlex

Two sex-linked fragments were identified by RAPD analyses in the dioecious diploid shrub Aucuba japonica var. ovoidea and were converted into markers of male-specific sequence characterized amplified region (SCAR) markers. PCRs using the primers designed in this study correctly discriminated 24 flowering males and 24 flowering females at higher annealing temperatures (SCAR markers OPA10-424 at 55 degrees C and OPN11-1095 at 65 degrees C), although at relatively low annealing temperatures, the fragments were amplified in both males and females. These SCAR primers were also tested to see whether they were applicable to sex identification in the conspecific tetraploid Aucuba japonica var. japonica. One set pf SCAR primers could be used for sex identification even in this tetraploid variety, although the other failed. The SCAR markers developed in this study will provide a powerful tool in identifying the sex of immature plants of dioecious A. japonica, which is a commercially valuable shrub due to its conspicuous fruits.

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: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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
GenreMethods

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
Published2009
Admission routes1
Has abstractyes

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