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Record W2133322751 · doi:10.2166/wst.2009.428

Analytical limits of three β-glucosidase-based commercial culture methods used in environmental microbiology, to detect enterococci

2009· article· en· W2133322751 on OpenAlex
Andrée F. Maheux, François J. Picard, Maurice Boissinot, Vicky Huppé, Luc Bissonnette, Jean-Luc T. Bernier, Philippe Cantin, Ann Huletsky, Michel G. Bergeron

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

VenueWater Science & Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsEnterococcusMicrobiologyBiologyAgarAgar plateBacteriaAntibiotics

Abstract

fetched live from OpenAlex

The enzyme-based test methods Enterolert, Chromocult Enterococci agar, and mEI agar, used to assess water quality through the detection Enterococcus spp., have been compared in terms of their analytical specificity and their ability to detect various enterococcal strains. To achieve this goal, we have tested 110 different non-enterococcal bacterial strains and 101 strains of Enterococcus spp. isolated from diverse origins. The results obtained showed that 69 (68.3%), 84 (83.2%), and 89 (88.1%) of the 101 enterococcal strains tested respectively yielded a positive signal with Enterolert, mEI, and Chromocult Enterococci. Regarding the specificity, none of the non-Enterococcus spp. strains tested were detectable by any of the three culture methods, except for Granulicatella adiacens which turned out positive on Chromocult Enterococci. The results of this study showed that, based on our collection of strains, the Enterolert test method detected less enterococcal strains than the two other methods.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.267
Teacher spread0.252 · 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