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Record W4307341847 · doi:10.1128/aac.00934-22

Ceftibuten-Ledaborbactam Activity against Multidrug-Resistant and Extended-Spectrum-β-Lactamase-Positive Clinical Isolates of <i>Enterobacterales</i> from a 2018–2020 Global Surveillance Collection

2022· article· en· W4307341847 on OpenAlexaff
James A. Karlowsky, Mark G. Wise, Meredith Hackel, Daniel C. Pevear, Greg Moeck, Daniel F. Sahm

Bibliographic record

VenueAntimicrobial Agents and Chemotherapy · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversity of Manitoba
FundersNational Institute of Allergy and Infectious DiseasesDivision of Intramural Research, National Institute of Allergy and Infectious Diseases
KeywordsMultiple drug resistanceMicrobiologyEnterobacteriaceaeVirologyMedicineBiologyAntibioticsEscherichia coliGeneticsGene

Abstract

fetched live from OpenAlex

Ceftibuten-ledaborbactam etzadroxil is a cephalosporin-boronate β-lactamase inhibitor prodrug combination under development as an oral treatment for complicated urinary tract infections caused by multidrug-resistant (MDR) Enterobacterales producing serine β-lactamases (Ambler class A, C, and D). In vivo , ledaborbactam etzadroxil (formerly VNRX-7145) is cleaved to the active inhibitor ledaborbactam (formerly VNRX-5236). To more completely define the breadth of ceftibuten-ledaborbactam’s activity against important antimicrobial-resistant pathogens, we assessed its in vitro activity against phenotypic and genotypic subsets from a 2018–2020 global culture collection of 3,889 clinical isolates of Enterobacterales , including MDR organisms, extended-spectrum-β-lactamase (ESBL)-positive organisms, and organisms that are nonsusceptible and resistant to other antimicrobials.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.254
Teacher spread0.247 · 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

Citations19
Published2022
Admission routes1
Has abstractyes

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