The HIV Risk Profiles of Latino Sexual Minorities and Transgender Persons Who Use Websites or Apps Designed for Social and Sexual Networking
Bibliographic record
Abstract
The use of websites and GPS-based mobile applications ("apps") designed for social and sexual networking has been associated with increased HIV risk; however, little is known about Latino sexual minorities' and transgender persons' use of these websites and apps and the risk profiles of those who use them compared with those who do not. Data from 167 participants who completed the baseline survey of a community-level HIV prevention intervention, which harnesses the social networks of Latino sexual minorities and transgender persons, were analyzed. One quarter of participants (28.74%, n = 48) reported using websites or apps designed for social and sexual networking, and 119 (71.26%) reported not using websites or apps designed for social and sexual networking. Those who used websites or apps were younger and reported more male sex partners, a sexually transmitted disease diagnosis, and illicit drug use other than marijuana. HIV prevention interventions for those who use websites or apps should consider addressing these risks for HIV.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".