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Record W2564240484 · doi:10.7717/peerj.2760

Pursuing the quest for better understanding the taxonomic distribution of the system of doubly uniparental inheritance of mtDNA

2016· article· en· W2564240484 on OpenAlexafffund
Arthur Gusman, Sophia Lecomte, Donald T. Stewart, Marco Passamonti, Sophie Breton

Bibliographic record

VenuePeerJ · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsAcadia UniversityUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaGroupe de recherche interuniversitaire en limnologie
KeywordsMitochondrial DNAEvolutionary biologyBiologyInheritance (genetic algorithm)GeneticsGene

Abstract

fetched live from OpenAlex

There is only one exception to strict maternal inheritance of mitochondrial DNA (mtDNA) in the animal kingdom: a system named doubly uniparental inheritance (DUI), which is found in several bivalve species. Why and how such a radically different system of mitochondrial transmission evolved in bivalve remains obscure. Obtaining a more complete taxonomic distribution of DUI in the Bivalvia may help to better understand its origin and function. In this study we provide evidence for the presence of sex-linked heteroplasmy (thus the possible presence of DUI) in two bivalve species, i.e., the nuculanoid Yoldia hyperborea (Gould, 1841) and the veneroid Scrobicularia plana (Da Costa , 1778), increasing the number of families in which DUI has been found by two. An update on the taxonomic distribution of DUI in the Bivalvia is also presented.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0010.002
Scholarly communication0.0020.006
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.028
GPT teacher head0.228
Teacher spread0.201 · 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

Citations111
Published2016
Admission routes2
Has abstractyes

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Same venuePeerJSame topicGenetic diversity and population structureFrench-language works237,207