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Record W2006692136 · doi:10.1136/bmj.333.7564.367

Rich nations are failing on universal access to antitretrovirals

2006· article· en· W2006692136 on OpenAlexaffabout
Jocalyn Clark

Bibliographic record

VenueBMJ · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHIV/AIDS Impact and Responses
Canadian institutionsToronto Public Health
Fundersnot available
KeywordsComputer scienceWorld Wide WebData scienceComputer securityMedicine

Abstract

fetched live from OpenAlex

The world's richest nations are failing to ensure that people living with HIV/AIDS in the developing world have universal access to antiretroviral drugs, delegates at the 16th international AIDS conference in Toronto were told this week. ![][1] “More funds are needed,” said Bill Gates, who spoke with his wife Melinda at the inauguration of the AIDS conference in Toronto Credit: JORGE UZON/AFP/GETTY IMAGES In an opening address, Microsoft founder Bill Gates said that he was making AIDS the top priority of his foundation, at which resources doubled last month to $62bn (£33bn; €49bn), after … [1]: /embed/graphic-1.gif

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)0.006
metaresearch head score (Gemma)0.022
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.042
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0040.004
Open science0.0000.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0420.005

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 head0.047
GPT teacher head0.297
Teacher spread0.250 · 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
GenreCommentary

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

Citations0
Published2006
Admission routes2
Has abstractyes

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