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Record W2953791328 · doi:10.1038/s42003-019-0490-7

Endangered island endemic plants have vulnerable genomes

2019· article· en· W2953791328 on OpenAlexfundno aff
Tomoko Hamabata, Gohta Kinoshita, Kazuki Kurita, Ping-Lin Cao, Motomi Itô, Jin Murata, Yoshiteru Komaki, Yuji Isagi, Takashi Makino

Bibliographic record

VenueCommunications Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and TechnologyResearch Organization of Information and Systems
KeywordsEndangered speciesGeographyEcologyEndemismBiologyHabitat

Abstract

fetched live from OpenAlex

Abstract Loss of genetic diversity is known to decrease the fitness of species and is a critical factor that increases extinction risk. However, there is little evidence for higher vulnerability and extinction risk in endangered species based on genomic differences between endangered and non-endangered species. This is true even in the case of functional loci, which are more likely to relate to the fitness of species than neutral loci. Here, we compared the genome-wide genetic diversity, proportion of duplicated genes (PD), and accumulation of deleterious variations of endangered island endemic (EIE) plants from four genera with those of their non-endangered (NE) widespread congeners. We focused on exhaustive sequences of expressed genes obtained by RNA sequencing. Most EIE species exhibited significantly lower genetic diversity and PD than NE species. Additionally, all endangered species accumulated deleterious variations. Our findings provide new insights into the genomic traits of EIE species.

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 score0.002
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.279
Teacher spread0.254 · 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

Citations60
Published2019
Admission routes1
Has abstractyes

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