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Record W2127209550 · doi:10.1183/09031936.00147507

Novel tests for diagnosing tuberculous pleural effusion: what works and what does not?

2008· review· en· W2127209550 on OpenAlex
Anete Trajman, Madhukar Pai, Keertan Dheda, Richard N. van Zyl-Smit, Alice Zwerling, Rajnish Joshi, Shriprakash Kalantri, Peter Daley, Dick Menzies

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

VenueEuropean Respiratory Journal · 2008
Typereview
Languageen
FieldMedicine
TopicPleural and Pulmonary Diseases
Canadian institutionsMcGill University
FundersMedical Research CouncilFogarty International CenterNational Institutes of HealthCanadian Institutes of Health ResearchNational Research Foundation
KeywordsMedicinePleural effusionPleural fluidTuberculosisDiagnostic testPathologySputumDiagnostic accuracyRadiology

Abstract

fetched live from OpenAlex

Tuberculous pleuritis is a common manifestation of extrapulmonary tuberculosis and is the most common cause of pleural effusion in many countries. Conventional diagnostic tests, such as microscopic examination of the pleural fluid, biochemical tests, culture of pleural fluid, sputum or pleural tissue, and histopathological examination of pleural tissue, have known limitations. Due to these limitations, newer and more rapid diagnostic tests have been evaluated. In this review, the authors provide an overview of the performance of new diagnostic tests, including markers of specific and nonspecific immune response, nucleic acid amplification and detection, and predictive models based on combinations of markers. Directions for future development and evaluation of novel assays and biomarkers for pleural tuberculosis are also suggested.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.088
GPT teacher head0.337
Teacher spread0.249 · 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