MétaCan
Menu
Back to cohort
Record W2614550113 · doi:10.3109/9781420087369-7

Antiretroviral therapy

2016· book-chapter· en· W2614550113 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsAntiretroviral therapyMedicineHuman immunodeficiency virus (HIV)VirologyViral load

Abstract

fetched live from OpenAlex

Injection drug use (IDU) was recognized as one of the major routes of transmission of HIV infection in the earliest days of the HIV/AIDS epidemic. In the early years of the epidemic in the United States, as many as one-third of all HIV-infected patients had acquired infection by means of IDU through needle sharing. In recent years, the number of individuals infected through IDU has declined. This decrease has been attributed both to the advent of effective antiretroviral therapy (ART) and to needle exchange programs in many areas of the country ( 1 , 2 ). Despite this change in the demographics and epidemiology of HIV/AIDS, however, the death rate from AIDS among injection drug users has risen ( 3 ). IDU remains an important route of transmission in other regions of the world. Eastern Europe and Central Asia saw a rapid rise in spread by this means beginning in the 1990s. The epidemic in those regions is now transforming and broadening to involve the sexual partners of injection drug users ( 4 ).

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.221
Threshold uncertainty score0.740

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2210.086

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.

Opus teacher head0.024
GPT teacher head0.255
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations7
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicHIV/AIDS drug development and treatmentFrench-language works237,207