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Glycopeptide Antibiotic Resistance

2002· review· en· W2145315186 on OpenAlex
Jeff Pootoolal, John M. Neu, Gerard D. Wright

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Annual Review of Pharmacology and Toxicology · 2002
Typereview
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGlycopeptideAntibioticsAntibiotic resistanceMicrobiologyVirulenceBiologyBacteriaGlycopeptide antibioticGeneComputational biologyVancomycinStaphylococcus aureusGenetics

Abstract

fetched live from OpenAlex

Glycopeptide antibiotics are integral components of the current antibiotic arsenal that is under strong pressures as a result of the emergence of a variety of resistance mechanisms over the past 15 years. Resistance has manifested itself largely through the expression of genes that encode proteins that reprogram cell wall biosynthesis and thus evade the action of the antibiotic in the enterococci, though recently new mechanisms have appeared that afford resistance and tolerance in the more virulent staphylococci and streptococci. Overcoming glycopeptide resistance will require innovative approaches to generate new antibiotics or otherwise to inhibit the action of resistance elements in various bacteria. The chemical complexity of the glycopeptides, the challenges of discovering and successfully exploiting new targets, and the growing number of distinct resistance types all increase the difficulty of the current problem we face as a result of the emergence of glycopeptide resistance.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.668
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.380
Teacher spread0.346 · 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