STI & HIV 2025 World Congress Conference Abstracts
Bibliographic record
Abstract
26-30 July 2025, Montreal, Canada The theme of the 2025 Congress is "Sexual Health for All", and we hope to gather together an inclusive group of researchers, clinicians, laboratorians, public health practitioners, community members, and advocates from around the world to share ground-breaking clinical and basic science, innovative public health interventions, and evidence-based best practices in STI/HIV. To cite the full set of abstracts: (2025) Abstracts from STI & HIV 2025 World Congress Conference. Sexual Health22, SHv22n4abs. doi:10.1071/SHv22n4abs To cite individual abstracts use the following format: McClarty L et al. (2025) OA10.05 - Expanded Polling Booth Surveys (ePBS) as a Rapid, Innovative, and Community-Engaged Tool for Routine Monitoring and Refinement of HIV/STI Programs for Criminalized and Other Marginalized Populations in Lower-Resourced Contexts: Findings from a Program Science-Guided Outcome Assessment in Nairobi County, Kenya [Conference abstract]. Sexual Health22, SHv22n4abs.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.581 | 0.184 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".