Bibliographic record
Abstract
Introduction African, Caribbean and Black (ACB) communities are disproportionately infected by HIV in Ontario, Canada. They constitute only 5% of the population of Ontario yet account for 25% of new diagnoses of HIV. The aim of this study is to understand underlying factors that augment the HIV risk in ACB communities and to inform policy and practice in Ontario. Methods and analysis We will conduct a cross-sectional study of first-generation and second-generation ACB adults aged 15–64 in Toronto (n=1000) and Ottawa (n=500) and collect data on sociodemographic information, sexual behaviours, substance use, blood donation, access and use of health services and HIV-related care. We will use dried blood spot testing to determine the incidence and prevalence of HIV infection among ACB people, and link participant data to administrative databases to investigate health service access and use. Factors associated with key outcomes (HIV infection, testing behaviours, knowledge about HIV transmission and acquisition, HIV vulnerability, access and use of health services) will be evaluated using generalised linear mixed models, adjusted for relevant covariates. Ethics and dissemination This study has been reviewed and approved by the following Research Ethics Boards: Toronto Public Health, Ottawa Public Health, Laurentian University; the University of Ottawa and the University of Toronto. Our findings will be disseminated as community reports, fact sheets, digital stories, oral and poster presentations, peer-reviewed manuscripts and social media.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.173 | 0.055 |
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".