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Record W2051647832 · doi:10.1177/1757177408099083

Reduction of bacterial contamination in a healthcare environment by silver antimicrobial technology

2009· article· en· W2051647832 on OpenAlexaff
Lesley Y. Taylor, Paul D. Phillips, Richard Hastings

Bibliographic record

VenueJournal of Infection Prevention · 2009
Typearticle
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsCanadian Society of Microbiologists
Fundersnot available
KeywordsAntimicrobialContaminationMedicineHuman decontaminationInfection controlBacteriaReduction (mathematics)MicrobiologyIntensive care medicineBiologyPathology

Abstract

fetched live from OpenAlex

This paper describes a pilot study undertaken in a major acute trust investigating reduction of bacterial contamination in a healthcare environment attributable to the use of silver antimicrobial (BioCote®) technology. The four month study assessed the impact of various BioCote®-treated products on the counts of viable bacteria cultured from the treated environment compared to a control. A mean reduction in bacterial counts of 95.8% was demonstrated on the BioCote®treated surfaces compared with untreated surfaces. A mean reduction of 43.5% was demonstrated on untreated products positioned in the same environment as BioCote®-treated products compared with control untreated products. This suggests decontamination is not limited to treated materials but can extend to the wider environment because of the presence of antimicrobial materials. In the light of increasing evidence implicating the role of the environment in healthcare acquired infection, the potential of BioCote®-treated products to provide an additional infection control mechanism is highlighted.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.689
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.009
GPT teacher head0.292
Teacher spread0.282 · 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

Citations36
Published2009
Admission routes1
Has abstractyes

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