MétaCan
Menu
← Back to cohort
Record W4389480114 · doi:10.1139/cjm-2023-0121

Wild fish from a highly urbanized river (Orge, France) as vectors of culturable <i>Enterobacterales</i> resistant to antibiotics

2023· article· en· W4389480114 on OpenAlexvenueno aff
Anne-Laure Vivant, Étienne Marchand, Benjamin Janvier, Thierry Berthe, Elodie Moreau-Guigon, Nathalie Grall, Fabrice Alliot, Aurélie Goutte, Fabienne Petit

Bibliographic record

VenueCanadian Journal of Microbiology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsnot available
FundersCentre National de la Recherche ScientifiqueIndian Council of Agricultural Research
KeywordsBiologyEnterobacterEscherichia coliMicrobiologyIntegronBacteriaAntibiotic resistanceAntibioticsKlebsiellaPopulationEnterobacteriaceaeKlebsiella pneumoniaeGeneticsGeneMedicine

Abstract

fetched live from OpenAlex

This study shows how wild fishes from urbanized rivers could be involved in the spread of antibiotic-resistant Enterobacterales. Antibiotic resistance profiles and molecular detection of clinical integron ( IntI1) were carried out on 105 Enterobacterales isolated from 89 wildfish (skin or gut) belonging to 8 species. The proportion of isolates resistant to at least one antibiotic was independent of fish species and reached 28.3% within the Escherichia coli ( E. coli) population and 84.7% in the non- E.coli Enterobacterales. Bacteria involved in nosocomial infections were isolated, such as E. coli, Klebsiella, and Enterobacter, as well as the environmental bacteria ( Lelliottia, Butiauxella, and Kluyvera).

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)0.000
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.006
GPT teacher head0.209
Teacher spread0.203 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Microbiology→Same topicAntibiotic Resistance in Bacteria→French-language works237,207→