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Record W2017240297 · doi:10.1371/journal.pone.0022495

Comparison of LED and Conventional Fluorescence Microscopy for Detection of Acid Fast Bacilli in a Low-Incidence Setting

2011· article· en· W2017240297 on OpenAlexafffund
Jessica Minion, Madhukar Pai, Andrew Ramsay, Dick Menzies, Christina Greenaway

Bibliographic record

VenuePLoS ONE · 2011
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsJewish General HospitalMcGill UniversityMontreal Clinical Research InstituteUniversity of Alberta
FundersJewish General HospitalEuropean and Developing Countries Clinical Trials PartnershipCanadian Institutes of Health ResearchEuropean Commission
KeywordsMicroscopeFluorescence microscopeMicroscopyOptical microscopeFluorescenceAcid-fastOpticsMaterials sciencePathologyMedicineTuberculosisPhysicsScanning electron microscopeSputum

Abstract

fetched live from OpenAlex

INTRODUCTION: Light emitting diode fluorescence microscopes have many practical advantages over conventional mercury vapour fluorescence microscopes, which would make them the preferred choice for laboratories in both low- and high-resource settings, provided performance is equivalent. METHODS: In a nested case-control study, we compared diagnostic accuracy and time required to read slides with the Zeiss PrimoStar iLED, LW Scientific Lumin, and a conventional fluorescence microscope (Leica DMLS). Mycobacterial culture was used as the reference standard, and subgroup analysis by specimen source and organism isolated were performed. RESULTS: There was no difference in sensitivity or specificity between the three microscopes, and agreement was high for all comparisons and subgroups. The Lumin and the conventional fluorescence microscope were equivalent with respect to time required to read smears, but the Zeiss iLED was significantly time saving compared to both. CONCLUSIONS: Light emitting diode microscopy should be considered by all tuberculosis diagnostic laboratories, including those in high income countries, as a replacement for conventional fluorescence microscopes. Our findings provide support to the recent World Health Organization policy recommending that conventional fluorescence microscopy be replaced by light emitting diode microscopy using auramine staining in all settings where fluorescence microscopy is currently used.

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)0.001
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 score0.107
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.087
GPT teacher head0.351
Teacher spread0.264 · 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

Citations45
Published2011
Admission routes2
Has abstractyes

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