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Record W2097653302 · doi:10.1186/1471-2180-12-40

Antagonistic interactions peak at intermediate genetic distance in clinical and laboratory strains of Pseudomonas aeruginosa

2012· article· en· W2097653302 on OpenAlexaff
Sijmen E. Schoustra, Jonathan Dench, Rola Dali, Shawn D. Aaron, Rees Kassen

Bibliographic record

VenueBMC Microbiology · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEvolutionary Game Theory and Cooperation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAntagonismBiologyCompetition (biology)Pseudomonas aeruginosaGenotypeImmune systemEcologyGeneticsMicrobiologyEvolutionary biologyBacteriaGene

Abstract

fetched live from OpenAlex

BACKGROUND: Bacteria excrete costly toxins to defend their ecological niche. The evolution of such antagonistic interactions between individuals is expected to depend on both the social environment and the strength of resource competition. Antagonism is expected to be weak among highly similar genotypes because most individuals are immune to antagonistic agents and among dissimilar genotypes because these are unlikely to be competing for the same resources and antagonism should not yield much benefit. The strength of antagonism is therefore expected to peak at intermediate genetic distance. RESULTS: We studied the ability of laboratory strains of Pseudomonas aeruginosa to prevent growth of 55 different clinical P. aeruginosa isolates derived from cystic fibrosis patients. Genetic distance was determined using genetic fingerprints. We found that the strength of antagonism was maximal among genotypes of intermediate genetic distance and we show that genetic distance and resource use are linked. CONCLUSIONS: Our results suggest that the importance of social interactions like antagonism may be modulated by the strength of resource competition.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.025
GPT teacher head0.331
Teacher spread0.306 · 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 designObservational
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

Citations28
Published2012
Admission routes1
Has abstractyes

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