Cohort Profile: The International Collaboration of Incident HIV and Hepatitis C in Injecting Cohorts (InC3) Study
Bibliographic record
Abstract
The International Collaboration of Incident HIV and Hepatitis C in Injecting Cohorts (InC(3)) Study is an international multi-cohort project of pooled biological and behavioural data from nine prospective cohorts of people who inject drugs (PWID). InC(3) brings together researchers from Australia, Canada, USA and the Netherlands with expertise in epidemiology, biostatistics, clinical and behavioural sciences, virology and immunology to investigate research questions relevant to hepatitis C virus (HCV) and HIV outcomes. InC(3) was established to: (i) create a merged multi-cohort study of pooled data from well-characterized cohorts of PWID with prospective data on HIV and HCV infections, with a particular focus on HCV; (ii) facilitate new studies not possible within individual cohorts; and (iii) bring together researchers across disciplines to answer a broad range of research questions. Study cohorts identify acute HCV cases through follow-up of high-risk HCV antibody-negative PWID or through clinical referral networks. To date, data from 1986 to 2010 have been received from all contributing cohorts, with 821 HCV-infected and 1216 HCV-uninfected participants (overall, n = 2037). Data collected include demographics, host genetics, HCV ribonucleic acid testing, alanine aminotransferase testing, HIV/hepatitis B virus testing, HCV therapy, loss to follow-up and mortality. Potential collaborators should contact the InC(3) PI Dr Kimberley Page (kPage@psg.ucsf.edu) for further information.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".