MétaCan
Menu
Back to cohort
Record W2097987563 · doi:10.1039/c2an35988j

A bacteriophage endolysin-based electrochemical impedance biosensor for the rapid detection of Listeria cells

2012· article· en· W2097987563 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Analyst · 2012
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLysinListeriaListeria monocytogenesBiosensorBacteriophageChemistryPeptidoglycanDielectric spectroscopyDetection limitMicrobiologyBacteriaElectrodeChromatographyElectrochemistryBiochemistryBiologyEnzymeEscherichia coli

Abstract

fetched live from OpenAlex

The objective of this study was to develop a biosensor using the cell wall binding domain (CBD) of bacteriophage-encoded peptidoglycan hydrolases (endolysin) immobilized on a gold screen printed electrode (SPE) and subsequent electrochemical impedance spectroscopy (EIS) for a rapid and specific detection of Listeria cells. The endolysin was amine-coupled to SPEs using EDC/NHS chemistry. The CBD-based electrode was used to capture and detect the Listeria innocua serovar 6b from pure culture and 2% artificially contaminated milk. In our study, the endolysin functionalized SPEs have been characterized using X-ray photoelectron spectroscopy (XPS). The integration of endolysin-based recognition for specific bacteria and EIS can be used for direct and rapid detection of Listeria cells with high specificity against non-Listeria cells with a limit of detection of 1.1 × 10(4) and 10(5) CFU mL(-1) in pure culture and 2% milk, respectively.

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 score0.087
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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