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Record W6929538470 · doi:10.5061/dryad.4xgxd2560

Data from: Interspecific hybrids show a reduced adaptive potential under DNA damaging conditions

2021· dataset· en· W6929538470 on OpenAlexafffund

Bibliographic record

VenueDRYAD · 2021
Typedataset
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversité Laval
FundersFonds de recherche du Québec – Nature et technologiesFonds de Recherche du Québec - Santé
KeywordsHybridStimulus (psychology)GenomeAdaptation (eye)YeastAdaptive evolutionInterspecific hybridization

Abstract

fetched live from OpenAlex

The data is framed in a context of experimental evolution. Popular Summary: Hybridization between species can be a dead end or a stimulus for adaptation and speciation. This stimulus could be fueled, among other things, by the intrinsic elevated rate of evolution of hybrid genomes. Whether this serves as an advantage for hybrids when faced with extreme stress is largely unknown. Here we tested this by evolving yeast species and their hybrids in UV mimetic conditions. We find that hybrids adapt slower than parental species in these conditions. We reason that this may be caused by the fact that the intrinsic genome instability of hybrids is pushed to levels above which it helps adaptive evolution.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.093
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.005

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 head0.043
GPT teacher head0.289
Teacher spread0.246 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2021
Admission routes2
Has abstractyes

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