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Antimicrobial resistance: a concise update

2024· review· en· 485 citations· W4402655854 on OpenAlex· 10.1016/j.lanmic.2024.07.010

Why is this work in the frame?

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

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

Full frame distilled prediction

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.

Candidate categories
Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Not applicableConsensus signal: Not applicable
Genre
Candidate signal: ReviewConsensus signal: Review
Teacher disagreement score
0.042
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.030
GPT teacher head0.321
Teacher spread
0.291 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Antimicrobial resistance (AMR) is a serious threat to global public health, with approximately 5 million deaths associated with bacterial AMR in 2019. Tackling AMR requires a multifaceted and cohesive approach that ranges from increased understanding of mechanisms and drivers at the individual and population levels, AMR surveillance, antimicrobial stewardship, improved infection prevention and control measures, and strengthened global policies and funding to development of novel antimicrobial therapeutic strategies. In this rapidly advancing field, this Review provides a concise update on AMR, encompassing epidemiology, evolution, underlying mechanisms (primarily those related to last-line or newer generation of antibiotics), infection prevention and control measures, access to antibiotics, antimicrobial stewardship, AMR surveillance, and emerging non-antibiotic therapeutic approaches. The Review also discusses the potential roles of artificial intelligence in addressing AMR, including antimicrobial susceptibility testing, AMR surveillance, antimicrobial stewardship, diagnosis, and antimicrobial drug discovery and development. This Review highlights the urgent need for addressing the global effects of AMR and for rapid advancement of relevant technology in this dynamic field.

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.

The record

Venue
The Lancet Microbe
Topic
Antibiotic Resistance in Bacteria
Field
Biochemistry, Genetics and Molecular Biology
Canadian institutions
University of British Columbia
Funders
HORIZON EUROPE European Research CouncilBirmingham Biomedical Research CentreInvention for InnovationMedical Research CouncilCanadian Institutes of Health ResearchHorizon 2020 Framework ProgrammePerelman School of Medicine, University of PennsylvaniaDefense Threat Reduction AgencyNational Institutes of HealthKillam TrustsImpact FundEuropean CommissionUniversity of British ColumbiaUniversity of PennsylvaniaProcter and GambleNational Institute of General Medical SciencesNational Institute for Health and Care ResearchUnited Therapeutics CorporationBrain and Behavior Research FoundationBirmingham Health PartnersHungarian Research Network
Keywords
AntimicrobialAntibiotic resistanceMicrobiologyBiologyAntibiotics
Has abstract in OpenAlex
yes