MétaCan
Menu
Back to cohort
Record W2168987130 · doi:10.1098/rspb.2005.3068

Unparallel diversification in bacterial microcosms

2005· article· en· W2168987130 on OpenAlexafffund
Jabus Tyerman, Naomi Havard, Gerda Saxer, Michael Travisano, Michael Doebeli

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaJames S. McDonnell Foundation
KeywordsDiversification (marketing strategy)MicrocosmBiologyPopularityEvolutionary biologyCompetition (biology)Experimental evolutionPhenotypeGeneticsEcologyGeneBusinessSocial psychologyPsychology

Abstract

fetched live from OpenAlex

Adaptive speciation has gained popularity as a fundamental process underlying the generation of diversity. We tested whether populations respond to similar forms of disruptive selection by diversifying in similar or parallel ways by investigating diversified populations of Escherichia coli B evolved in glucose and glucose-acetate environments. In both environments, the populations have differentiated into two phenotypes, named for their characteristic colony morphologies: large (L) and small (S). Each type is heritable and this polymorphism (or 'diversified pair') appears to be maintained by negative frequency dependence. The L and S phenotypes from different environments are convergent in their colony morphology and growth characteristics. We tested whether diversification was parallel by conducting competition experiments between L and S types from different environments. Our results indicate that replicate diversified pairs from different environments have not diversified in parallel ways and suggest that subtle differences in evolutionary environment can crucially affect the outcome of adaptive diversification.

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)0.002
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.015
GPT teacher head0.240
Teacher spread0.226 · 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

Citations38
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Royal Society B Biological SciencesSame topicEvolution and Genetic DynamicsFrench-language works237,207