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Record W2791561244 · doi:10.1093/femsle/fny026

Diversification of Pseudomonas aeruginosa within the cystic fibrosis lung and its effects on antibiotic resistance

2018· review· en· W2791561244 on OpenAlexafffund
Shawn T. Clark, David S. Guttman, David Hwang

Bibliographic record

VenueFEMS Microbiology Letters · 2018
Typereview
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsUniversity of TorontoToronto General HospitalCanada Research ChairsUniversity Health Network
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsPseudomonas aeruginosaCystic fibrosisAntibiotic resistanceBiologyAntibioticsMicrobiologyAntimicrobialGenetic diversityBacteriaGeneticsMedicinePopulation

Abstract

fetched live from OpenAlex

The evolution and diversification of bacterial pathogens within human hosts represent potential barriers to the diagnosis and treatment of life-threatening infections. Tremendous genetic and phenotypic diversity is characteristic of host adaptation in strains of Pseudomonas aeruginosa that infect the airways of individuals with chronic lung diseases and prove to be extremely difficult to eradicate. In this MiniReview, we examine recent advances in understanding within-host diversity and antimicrobial resistance in P. aeruginosa populations from the lower airways of individuals with the fatal genetic disease cystic fibrosis and the potential impacts that this diversity may have on detecting and interpreting antimicrobial susceptibility within these populations.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.823
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.299
Teacher spread0.280 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations34
Published2018
Admission routes2
Has abstractyes

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