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Record W2799440651 · doi:10.1371/journal.pgen.1007249

A less selfish view of genome size evolution in maize

2018· letter· en· W2799440651 on OpenAlexafffund
Julia M. Kreiner, Stephen Wright

Bibliographic record

VenuePLoS Genetics · 2018
Typeletter
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyGenomeEvolutionary biologyGeneticsGenome sizeComputational biologyGene

Abstract

fetched live from OpenAlex

Genome size varies by many orders of magnitude across plants and animals, but resolving the most important evolutionary forces driving this variation remains challenging. Since eukaryotic genome size variation is not associated with complexity, genetic drift of the amount of noncoding DNA could dominate, implicating population and species history as key drivers of shifts in DNA content. Alternatively, directional selection could be acting on DNA content, but if so, it has not been resolved which level of selection is most important. Since the predominant component of many eukaryotic genomes is comprised of selfish genetic elements such as transposable elements (TEs) and regions subject to meiotic drive, factors that influence their differential success across populations and species could account for much of the variation in genome size. However, DNA content can also have important effects on organismal phenotype that could be under directional selection. Genome size may often be an important determinant of cell size and division rate and the subject of selection via its effects on developmental and metabolic phenotypes Supporting this view, correlations of genome size with invasive potential and growth rate [3], regional abundance and seed size In this issue, Bilinski et al.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.820
Threshold uncertainty score0.787

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 integrity0.0010.000
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 head0.029
GPT teacher head0.207
Teacher spread0.178 · 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 designNot applicable
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

Citations4
Published2018
Admission routes2
Has abstractyes

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