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Record W2606629520 · doi:10.1139/cjm-2017-0119

Frogs host faecal bacteria typically associated with humans

2017· article· en· W2606629520 on OpenAlexvenueno aff
Karen Gibb, Xavier Schobben, Keith A. Christian

Bibliographic record

VenueCanadian Journal of Microbiology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
FundersCharles Darwin UniversityUniverzita Karlova v Praze
KeywordsBiologyBacteroides thetaiotaomicronBacteroidesSewageFecesBacteriaHost (biology)Enterococcus faeciumMicrobiologyEnterococcusContaminationEcologyZoologyIndicator bacteriaFecal coliformWater qualityEnvironmental science

Abstract

fetched live from OpenAlex

Tree frogs commonly access drinking water tanks; this may have human health implications. Although amphibians might not be expected to host mammalian faecal indicator bacteria (FIB), it is possible that they may have human FIB on their skin after exposure to human waste. We collected faeces and skin wash from green tree frogs (Litoria caerulea) from a natural environment, a suburban site, and a suburban site near a creek occasionally contaminated with sewage effluent. We used molecular techniques to test for FIB that are routinely used to indicate human faecal contamination. Enterococci colonies were isolated from both faecal and skin wash samples, and specific markers (Enterococcus faecium and Bacteroides thetaiotaomicron) were found in frog faeces, demonstrating that these markers are not human- or mammalian-specific. Bacteroides thetaiotaomicron was detected in frogs from both natural and urban sites, but E. faecium was only associated with the sewage impacted site.

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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.020
GPT teacher head0.242
Teacher spread0.222 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Microbiology→Same topicPharmaceutical and Antibiotic Environmental Impacts→French-language works237,207→