Cohort Profile: Antiretroviral Therapy Cohort Collaboration (ART-CC)
Bibliographic record
Abstract
The advent of effective combination antiretroviral therapy (ART) in 1996 resulted in fewer patients experiencing clinical events, so that some prognostic analyses of individual cohort studies of human immunodeficiency virus-infected individuals had low statistical power. Because of this, the Antiretroviral Therapy Cohort Collaboration (ART-CC) of HIV cohort studies in Europe and North America was established in 2000, with the aim of studying the prognosis for clinical events in acquired immune deficiency syndrome (AIDS) and the mortality of adult patients treated for HIV-1 infection. In 2002, the ART-CC collected data on more than 12,000 patients in 13 cohorts who had begun combination ART between 1995 and 2001. Subsequent updates took place in 2004, 2006, 2008, and 2010. The ART-CC data base now includes data on more than 70,000 patients participating in 19 cohorts who began treatment before the end of 2009. Data are collected on patient demographics (e.g. sex, age, assumed transmission group, race/ethnicity, geographical origin), HIV biomarkers (e.g. CD4 cell count, plasma viral load of HIV-1), ART regimen, dates and types of AIDS events, and dates and causes of death. In recent years, additional data on co-infections such as hepatitis C; risk factors such as smoking, alcohol and drug use; non-HIV biomarkers such as haemoglobin and liver enzymes; and adherence to ART have been collected whenever available. The data remain the property of the contributing cohorts, whose representatives manage the ART-CC via the steering committee of the Collaboration. External collaboration is welcomed. Details of contacts are given on the ART-CC website (www.art-cohort-collaboration.org).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".