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Record W2126903712 · doi:10.1186/1742-6405-11-28

Highlights from the 2014 International Symposium on HIV & Emerging Infectious Diseases (ISHEID): from cART management to the end of the HIV pandemic

2014· article· en· W2126903712 on OpenAlexaff
Alain Lafeuillade, Mark A. Wainberg, Marie‐Lise Gougeon, Sabine Kinloch‐de Loes, Philippe Halfon, Hervé Tissot‐Dupont

Bibliographic record

VenueAIDS Research and Therapy · 2014
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicinePandemicHuman immunodeficiency virus (HIV)CartCoinfectionDiseaseInfectious disease (medical specialty)Antiretroviral therapyIntensive care medicineImmunologyCoronavirus disease 2019 (COVID-19)VirologyViral loadPathology

Abstract

fetched live from OpenAlex

The 2014 International Symposium on HIV and Emerging Infectious Diseases (ISHEID) provided a forum for investigators to hear the latest research developments in the clinical management of HIV and HCV infections as well as HIV cure research. Combined anti-retroviral therapy (c-ART) has had a profound impact on the disease prognosis and transformed this infection into a chronic disease. However, HIV is able to persist within the infected host and the pandemic is still growing. The main 2014 ISHEID theme was, hence "Together for a world without HIV and AIDS". In this report we not only give details on this main topic but also summarize what has been discussed in the areas of HCV coinfection and present a short summary on currently emerging viral diseases.

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)0.004
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.014
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0140.005

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 head0.034
GPT teacher head0.343
Teacher spread0.310 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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