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Record W2604658774 · doi:10.1093/femsec/fix046

Antagonistic interactions of soil pseudomonads are structured in time

2017· article· en· W2604658774 on OpenAlexaff
Susanne A. Kraemer, Jean‐Paul Soucy, Rees Kassen

Bibliographic record

VenueFEMS Microbiology Ecology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of OttawaOntario Genomics
Fundersnot available
KeywordsBiologyEcosystemPseudomonasEcologySoil microbiologyMicrobiologyBacteriaSoil waterGenetics

Abstract

fetched live from OpenAlex

Social interactions have been invoked as potential major selective forces structuring natural microbial communities and thus may help explain the astonishing bacterial diversity of natural ecosystems. Here, we investigate the prevalence and structure of exotoxin-mediated antagonistic interactions among free-living soil Pseudomonas strains collected over the course of 2 years at distances of up to 1 km. Unlike some previous studies on antagonistic interactions among natural isolates, we found the prevalence of exotoxin-mediated inhibitions to be relatively low. When present, antagonistic interactions show a weakly positive relationship with genetic relatedness and metabolic similarity. Isolates sampled from the same growing season were significantly more likely to inhibit each other than they were to inhibit isolates from different growing seasons. Exotoxin-mediated antagonistic interactions between soil pseudomonads thus seem to be structured in time but do not appear to be a major selective force shaping free-living soil bacterial communities of pseudomonads.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.008
GPT teacher head0.245
Teacher spread0.237 · 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 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

Citations13
Published2017
Admission routes1
Has abstractyes

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