An International Collaboration To Standardize HIV-2 Viral Load Assays: Results from the 2009 ACHI <sub>E</sub> V <sub>2E</sub> Quality Control Study
Bibliographic record
Abstract
Accurate HIV-2 plasma viral load quantification is crucial for adequate HIV-2 patient management and for the proper conduct of clinical trials and international cohort collaborations. This study compared the homogeneity of HIV-2 RNA quantification when using HIV-2 assays from ACHI(E)V(2E) study sites and either in-house PCR calibration standards or common viral load standards supplied to all collaborators. Each of the 12 participating laboratories quantified blinded HIV-2 samples, using its own HIV-2 viral load assay and standard as well as centrally validated and distributed common HIV-2 group A and B standards (http://www.hiv.lanl.gov/content/sequence/HelpDocs/subtypes-more.html). Aliquots of HIV-2 group A and B strains, each at 2 theoretical concentrations (2.7 and 3.7 log(10) copies/ml), were tested. Intralaboratory, interlaboratory, and overall variances of quantification results obtained with both standards were compared using F tests. For HIV-2 group A quantifications, overall and interlaboratory and/or intralaboratory variances were significantly lower when using the common standard than when using in-house standards at the concentration levels of 2.7 log(10) copies/ml and 3.7 log(10) copies/ml, respectively. For HIV-2 group B, a high heterogeneity was observed and the variances did not differ according to the type of standard used. In this international collaboration, the use of a common standard improved the homogeneity of HIV-2 group A RNA quantification only. The diversity of HIV-2 group B, particularly in PCR primer-binding regions, may explain the heterogeneity in quantification of this strain. Development of a validated HIV-2 viral load assay that accurately quantifies distinct circulating strains is needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.147 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".