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Record W2106281950 · doi:10.1139/cjb-2015-0025

Genetic structure of <i>Quercus gilva</i> Blume in Japan as revealed by chloroplast DNA sequences

2015· article· en· W2106281950 on OpenAlexvenueno aff
Nami Sugiura, Ding‐Qin Tang, Hiroyuki Kurokochi, Yoko Saito, Yuji Ide

Bibliographic record

VenueBotany · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsnot available
FundersTaiwan Forestry Research Institute
KeywordsHaplotypeChloroplast DNABiologyPopulationGeneticsGenetic structureEvolutionary biologyChloroplastGenetic variationGeneGenotypeDemography

Abstract

fetched live from OpenAlex

Quercus gilva (Blume) is an evergreen oak species that is native to Japan, China, and Taiwan. Because of a long history of human impact, this species is threatened with extinction in several regions of Japan. The objective of this study was to identify the genetic structure of Q. gilva based on chloroplast DNA (cpDNA) sequencing analysis. We collected 123 samples from 25 populations in Japan, 8 samples from 1 population in China, and 46 samples from 5 populations in Taiwan. Approximately 1815 bp of cpDNA was sequenced for each of the 177 samples. Thirteen haplotypes were detected, with no cross-region distribution of haplotypes among the three geographically separated countries. There were large genetic differences among populations (G ST = 0.824, [Formula: see text] = 0.937). Six haplotypes (haplotypes 1, 2, 3, 4a, 4b, and 5) were detected in Japan; haplotype 4a was the most common, detected from 20 populations, and the other rare haplotypes, except for haplotype 4b, occurred at the edge of the species’ distribution. In addition, four haplotypes (haplotypes 1, 2, 3, and 5) were quite different from the predominant haplotype (haplotype 4a), with more than four cpDNA mutations except for a mononucleotide repeat, suggesting that populations with these rare haplotypes should be conserved separately.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.638

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 head0.008
GPT teacher head0.220
Teacher spread0.212 · 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

Citations11
Published2015
Admission routes1
Has abstractyes

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