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Record W2344410868 · doi:10.1109/jlt.2016.2532466

Bacteriophage Adhesin-Coated Long-Period Grating-Based Sensor: Bacteria Detection Specificity

2016· article· en· W2344410868 on OpenAlexafffund
Marcin Koba, Mateusz Śmietana, Ewa Brzozowska, Sabina Górska, Monika Janik, Predrag Mikulic, Andrea Cusano, Wojtek J. Bock

Bibliographic record

VenueJournal of Lightwave Technology · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversité du Québec en Outaouais
FundersNarodowe Centrum NaukiNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsBiosensorSalmonella entericaBacteriophageEscherichia coliBacteriaBacterial adhesinSalmonellaMicrobiologyCladding (metalworking)Materials scienceChemistryBiologyNanotechnologyBiochemistryGene

Abstract

fetched live from OpenAlex

In this paper, we study a label-free detection specificity of an optical fiber long-period grating (LPG) biosensor working near the dispersion turning point of higher order cladding modes. The LPG sensor is functionalized with bacteriophage adhesin and tested with specific and nonspecific bacteria dry weights. It is shown that that such a biosensor is able to selectively bind to specific bacterial strains. In the experiments bacteria dry weights of E. coli B were used as a positive test and E. coli K12 and Salmonella enterica as negative tests. The resonance wavelength shift induced by E. coli B reaches over 90 nm, while for E. coli K12 and Salmonella enterica approximately 40 and 20 nm, respectively. Additionally, whole-cell-ELISA tests were made to confirm LPG-based biosensor outcomes, and numerical simulations were conducted to estimate biolayer impact on sensor's performance.

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 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 score0.062
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations26
Published2016
Admission routes2
Has abstractyes

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