The Changing Trend of HIV Type 1 Subtypes in Nairobi
Bibliographic record
Abstract
Monitoring the distribution of HIV-1 subtypes and recombinants among infected individuals has become a priority in HIV therapy. A laboratory analysis of samples collected from HIV-positive patients attending an STI clinic in Nairobi was done between March and May 2004. PCR was carried out on pol (intergrase) and env (C2V3) regions and resulting data on the 54 samples successfully analyzed revealed the following as circulating subtypes: 35/54(65%) were A1/A1, 5/54(9%) were A/C, 4/54 (7%) were A1/D, 1/54 (2%) was C/D, 1/54 (2%) was D/D, 1/54 (2%) was A1/A2, 1/54 (2%)was G/G, 1/54 (2%) was A2/D, 1/54 (2%) was C/C, and 4/54 (7%) were CRF02_ AG. The results show an increase in HIV-1 recombinants with the emergence of A1/A2 and an increase in CRF02_AG recombinants. Subtype diversity in the advent of ARV use will impact negatively on treatment outcomes. As such, increased viral evolution and recombination will call for continuous evaluation of available anti-HIV regimens for better management of those infected with HIV-1.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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 | 0.000 |
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.
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".