Discrepancies in Assignment of Subtype/Recombinant Forms by Genotyping Programs for HIV Type 1 Drug Resistance Testing May Falsely Predict Superinfection
Bibliographic record
Abstract
With the growing diversity of the HIV pandemic, routine genotyping is an important tool for monitoring viral subtype as well as drug resistance. In this regard, numerous subtyping tools and drug resistance algorithms are available online. However, there are discrepancies in the use of these online tools in the designation of HIV-1 subtypes or recombinant forms that may have an impact on drug susceptibility profiles. Indeed, inconsistencies in some of these tools may lead to a false designation of dual infection and/or superinfection. In this case study, we evaluated the sequence diversity of an infection that was referred to us as a potential case of superinfection as a result of variations in designation of subtype. We evaluated sequences using five different online tools and finally determined by phylogenetic analysis that the sequence was a unique A1/C intersubtype recombinant at baseline and not a case of superinfection.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".