MétaCan
Menu
Back to cohort
Record W2424560189 · doi:10.1111/ele.12566

The ghosts of selection past reduces the probability of plastic rescue but increases the likelihood of evolutionary rescue to novel stressors in experimental populations of wild yeast

2016· article· en· W2424560189 on OpenAlexafffund
Pedram Samani, Graham Bell

Bibliographic record

VenueEcology Letters · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFungal and yeast genetics research
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsStressorBiologyAdaptation (eye)Genetic FitnessExperimental evolutionEcologySelection (genetic algorithm)Evolutionary biologyZoologyBiological evolutionGeneticsGene

Abstract

fetched live from OpenAlex

Persistence by adaptation is called evolutionary rescue. Evolutionary rescue is more likely in populations that have been previously exposed to lower doses of the same stressor. Environmental fluctuations might also reduce the possibility of rescue, but little is known about the effect of evolutionary history on the likelihood of rescue. In this study, we hypothesised that the ubiquitous operation of generalised stress responses in many organisms increases the likelihood of rescue after exposure to other stressors. We tested this hypothesis with experimental populations that had been exposed to long-term starvation and were then selected on different, unrelated stressors. We found that prior adaptation to starvation imposes contrary effects on the plastic and evolutionary responses of populations to subsequent stressors. When first exposed to new stressors, such populations become extinct more often. If they survive the initial exposure to the new stressors, however, they are more likely to undergo evolutionary rescue.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.015
GPT teacher head0.267
Teacher spread0.251 · 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 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

Citations22
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueEcology LettersSame topicFungal and yeast genetics researchFrench-language works237,207