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Record W4403307024 · doi:10.1093/jtm/taae131

Antimicrobial resistance genes acquisition among Dutch intercontinental travellers: a prospective multicentre study

2024· article· en· W4403307024 on OpenAlexaff
Jiyang Chan, Niels van Best, Maris S. Arcilla, Jarne van Hattem, Damian C. Melles∗, Menno D. de Jong, Constance Schultsz, Perry J.J. van Genderen, Martin Bootsma, Abraham Goorhuis, Martin P. Grobusch, Astrid M. Oude Lashof, Henri A. Verbrugh, John Penders, Astrid Oude Lashof

Bibliographic record

VenueJournal of Travel Medicine · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsInstitute of Infection and Immunity
FundersNederlandse Organisatie voor Wetenschappelijk OnderzoekZonMw
KeywordsMedicineAntibiotic resistanceEnvironmental healthAntimicrobialShellfishProspective cohort studyTravel medicineAntibioticsMicrobiologyInternal medicineFisheryFish <Actinopterygii>Pathology

Abstract

fetched live from OpenAlex

Antimicrobial resistance (AMR) is a significant global health threat. People often acquire AMR bacteria during travel and import them into their home countries. This large-scale cohort study among intercontinental travellers identified destination, diarrhoea, antibiotic use, and shellfish consumption during travel as significant risk factors for acquisition of various AMR genes.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.285
Teacher spread0.270 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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