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Adaptation of experimental yeast populations to stressful conditions in relation to population size

2010· article· en· W2101803028 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Evolutionary Biology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyAdaptation (eye)PopulationStrain (injury)Selection (genetic algorithm)Population sizeYeastExperimental evolutionEvolutionary biologyEcologyGeneticsDemographyGeneAnatomy

Abstract

fetched live from OpenAlex

The purpose of this experiment was to find out how a population becomes adapted to extremely stressful conditions as its environment deteriorates. We created a deteriorating environment for experimental selection lines of yeast by a stepwise increase in the concentration of salt in the growth medium. After each step, we tested the ability of the lines to grow at a high concentration of salt near the lethal limit for the ancestral strain. We found that mutations enhancing growth in this highly stressful environment began to spread at intermediate salt concentrations. The degree of enhancement was related to effective population size by a power law with a small exponent. The effect size of these mutations also increased with the population size in a similar fashion. From these results, we interpret adaptation to lethal stress as an indirect response to selection for resistance to previous lower levels of stress in a deteriorating environment. This suggests that the pattern of genetic correlation between successively higher levels of stress is an important factor in facilitating 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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.860
Threshold uncertainty score0.363

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.304
Teacher spread0.291 · 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