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Record W2053012821 · doi:10.1002/jemt.20614

Rapid detection of microorganisms with nanoparticles and electron microscopy

2008· article· en· W2053012821 on OpenAlex
Ghinwa Naja, Sabahudin Hrapovic, Keith B. Male, Pierre Bouvrette, John H. T. Luong

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

VenueMicroscopy Research and Technique · 2008
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsNational Research Council CanadaBiotechnology Research InstituteMcGill University
Fundersnot available
KeywordsRhodococcus rhodochrousNanoparticleRaman spectroscopyScanning electron microscopeChemistryColloidal goldMicroorganismSodium borohydrideNuclear chemistryElectron microscopeMaterials scienceChromatographyNanotechnologyBacteriaRhodococcusBiochemistryBiologyOptics

Abstract

fetched live from OpenAlex

Rapid detection of microorganisms is highly desirable. A procedure has been developed based on interactions between gold nanoparticles and proteins of microorganisms (Escherichia coli, Rhodococcus rhodochrous, and Candida sp.) followed by scanning electron microscopy (SEM). The nanoparticle-cell interaction was confirmed by ultraviolet resonance Raman spectroscopy (UVRS) in the SEM focus. Cell suspensions in a buffer were interacted with gold nanoparticles (<10 nm in diameter) prepared from tetrachloroauric acid and sodium borohydride. Possible interference of elevated salt concentrations was eliminated by dialysis in deionized water. Small (10 microL) aliquots of cell-nanoparticle suspensions were dried on a silicon wafer and photographed under an SEM. Characteristic bacterial or yeast cell images in the micrographs indicated the actual presence of microorganisms in the suspension examined. This was further confirmed by UV resonance Raman spectroscopy.

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 score0.002
Threshold uncertainty score0.412

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 head0.016
GPT teacher head0.283
Teacher spread0.267 · 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