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Record W4244481576 · doi:10.1002/14651858.cd009184

Nucleic acid amplification techniques (NAATs) for early diagnosis of HIV-1 and HIV-2 infections

2011· reference-entry· en· W4244481576 on OpenAlexaff
Regina El Dib, Mariska Leeflang, Joseph L. Mathew, Ricardo AMB Almeida, David Salomão Lewi, Anil Kapoor, Sérgio Swain Müller, Ricardo Sobhie Diaz

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2011
Typereference-entry
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNucleic Acid Amplification TestsDiagnostic accuracyDiagnostic testHuman immunodeficiency virus (HIV)MedicineHIV diagnosisStage (stratigraphy)ImmunologyVirologyInternal medicineBiologyPediatricsAntiretroviral therapyViral load

Abstract

fetched live from OpenAlex

This is a protocol for a Cochrane Review (Diagnostic test accuracy). The objectives are as follows: Our primary objective is to assess the diagnostic accuracy (sensitivity and specificity) of NAATs (both quantitative and qualitative) for early diagnosis of people of all ages with suspected HIV‐1 and ‐2 infections. We hypothesize that their accuracy for early diagnosis will be as good as the diagnosis at a later stage. We furthermore hypothesize that there will be no differences in diagnostic accuracy between the different molecular tests when evaluated against the same reference standard. We defined early detection as a period that is consistently between one and three weeks (Busch 1997; Fiebig 2003).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.035
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.061
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0090.008
Bibliometrics0.0160.014
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0350.003

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 head0.084
GPT teacher head0.341
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations0
Published2011
Admission routes1
Has abstractyes

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