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Record W2119428590 · doi:10.1017/s146625230800159x

Antimicrobial resistance: its emergence and transmission

2008· review· en· W2119428590 on OpenAlex

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

VenueAnimal Health Research Reviews · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversity of GuelphPublic Health Agency of Canada
Fundersnot available
KeywordsHorizontal gene transferSelection (genetic algorithm)Mobile genetic elementsBiologyComputational biologyPlasmidGeneAntibiotic resistanceGeneticsTransmission (telecommunications)Evolutionary biologyData scienceComputer scienceGenomeArtificial intelligence

Abstract

fetched live from OpenAlex

New concepts have emerged in the past few years that help us to better understand the emergence and spread of antimicrobial resistance (AMR). These include, among others, the discovery of the mutator state and the concept of mutant selection window for resistances emerging primarily through mutations in existing genes. Our understanding of horizontal gene transfer has also evolved significantly in the past few years, and important new mechanisms of AMR transfer have been discovered, including, among others, integrative conjugative elements and ISCR (insertion sequences with common regions) elements. Simultaneously, large-scale studies have helped us to start comprehending the immense and yet untapped reservoir of both AMR genes and mobile genetic elements present in the environment. Finally, new PCR- and DNA sequencing-based techniques are being developed that will allow us to better understand the epidemiology of classical vectors of AMR genes, such as plasmids, and to monitor them in a more global and systematic way.

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)0.003
metaresearch head score (Gemma)0.000
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 score0.775
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.258
GPT teacher head0.494
Teacher spread0.236 · 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