The Relationships between Ethnicity, Sex, Risk Group, and Virus Load in Human Immunodeficiency Virus Type 1 Antiretroviral‐Naive Patients
Bibliographic record
Abstract
This cross-sectional study examined the relationships between ethnicity, sex, risk group, and virus load in human immunodeficiency virus type 1 (HIV-1) antiretroviral-naive patients. HIV-1 RNA levels were measured in 322 patients attending St. Thomas' Hospital between May 1997 and February 1999. By univariate analyses, only clinical status and CD4(+) cell count were related to virus load. In multivariate analysis, variables independently related to virus load were CD4(+) cell count (P=.001), being black African (P=.001), having a nonsexual risk for HIV infection (P=.03), and having AIDS (P=.05). Neither sex nor age was a significant predictor of initial virus load after adjusting for other variables. For a given CD4(+) cell count, black Africans and people who contracted HIV nonsexually presented with a virus load lower than that of patients in other groups. Because virus loads may need to be interpreted differently according to ethnicity, this may affect decisions on when to initiate antiretroviral therapy and how to interpret clinical trial results.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".