Determinants of Protection among HIV‐Exposed Seronegative Persons: An Overview
Bibliographic record
Abstract
Both clinical experience and a growing medical literature indicate that some persons who have been exposed to human immunodeficiency virus (HIV) infection remain uninfected. Although in some instances this may represent good fortune, cohorts of uninfected persons have been reported who are considered at high risk for infection. In these cohorts a variety of characteristics have been proposed as mediating protection, but to date only the 32–base pair deletion in the chemokine (C‐C motif) receptor 5 gene, which results in complete failure of cell surface expression of this coreceptor, has been associated with high‐level protection from HIV infection. With this in mind, there are probably many other factors that may individually or in combination provide some level of protection from acquisition of HIV infection. Because some of these factors are probably incompletely protective or inconsistently active, identifying them with confidence will be difficult. Nonetheless, clarifying the determinants of protection against HIV infection is a high priority that will require careful selection of high‐risk uninfected cohorts, who should undergo targeted studies of plausible mediators and broad screening for unexpected determinants of protection.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".