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Record W2116716923 · doi:10.1002/mbo3.141

Developing an international <i>Pseudomonas aeruginosa</i> reference panel

2013· article· en· W2116716923 on OpenAlexaff
Anthony De Soyza, Amanda J. Hall, Eshwar Mahenthiralingam, Pavel Dřevı́nek, Wiesław Kaca, Zuzanna Drulis‐Kawa, Stoyanka Stoitsova, Veronika Tóth, Tom Coenye, James E. A. Zlosnik, Jane L. Burns, Isabel Sá‐Correia, Daniël De Vos, Jean‐Paul Pirnay, Timothy J. Kidd, David W. Reid, Jim Manos, Jens Klockgether, Lutz Wiehlmann, Burkhard Tümmler, Siobhán McClean, Craig Winstanley

Bibliographic record

VenueMicrobiologyOpen · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthUniversiteit GentAlere
KeywordsVirulencePseudomonas aeruginosaBiologyMicrobiologyPathogenSerotypeOrganismOpportunistic pathogenGenotypeBacteriaGeneticsGene

Abstract

fetched live from OpenAlex

Pseudomonas aeruginosa is a major opportunistic pathogen in cystic fibrosis (CF) patients and causes a wide range of infections among other susceptible populations. Its inherent resistance to many antimicrobials also makes it difficult to treat infections with this pathogen. Recent evidence has highlighted the diversity of this species, yet despite this, the majority of studies on virulence and pathogenesis focus on a small number of strains. There is a pressing need for a P. aeruginosa reference panel to harmonize and coordinate the collective efforts of the P. aeruginosa research community. We have collated a panel of 43 P. aeruginosa strains that reflects the organism's diversity. In addition to the commonly studied clones, this panel includes transmissible strains, sequential CF isolates, strains with specific virulence characteristics, and strains that represent serotype, genotype or geographic diversity. This focussed panel of P. aeruginosa isolates will help accelerate and consolidate the discovery of virulence determinants, improve our understanding of the pathogenesis of infections caused by this pathogen, and provide the community with a valuable resource for the testing of novel therapeutic agents.

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)0.037
metaresearch head score (Gemma)0.030
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0080.005
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0040.005
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0090.008

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 head0.034
GPT teacher head0.262
Teacher spread0.228 · 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

Citations114
Published2013
Admission routes1
Has abstractyes

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