A Cross-Sectional, Retrospective Evaluation of Opt-Out Sexually Transmitted Infection Screening at Admission in a Short-Term Correctional Facility in Alberta, Canada
Bibliographic record
Abstract
Incarcerated populations experience higher rates of sexually transmitted infections (STIs) than the general population, alongside inconsistent testing strategies. In response, universal opt-out STIs (chlamydia, gonorrhea, syphilis, and HIV) screening was implemented at admission in a short-term correctional facility in Alberta, Canada, for individuals ≤35 years. A cross-sectional, retrospective evaluation of testing outcomes between March 2018 and February 2020 was completed. Descriptive statistics were used to stratify STIs by gender, age group, and date for univariate analysis. Despite low uptake (31.2%), opt-out screening resulted in high positivity rates (14.9%, 10.8%, 29.5%, and 0.3%, respectively) and treatment completion (93.7%) while capturing a high proportion (52.6%) of asymptomatic cases. Opt-out screening at admission is feasible and can improve STI testing in high-risk individuals experiencing incarceration in Canada.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 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".