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Record W2558446330 · doi:10.1056/nejmoa1602046

Safety and Efficacy of a Dapivirine Vaginal Ring for HIV Prevention in Women

2016· article· en· W2558446330 on OpenAlexaff
Annaléne Nel, Neliëtte van Niekerk, Saidi Kapiga, Linda‐Gail Bekker, Cynthia Gama, Katherine Gill, Anatoli Kamali, Philip Kotze, Cheryl Louw, Zonke Mabude, Nokuthula Miti, Sylvia Kusemererwa, Hugo Tempelman, Hannelie Carstens, Bríd Devlin, Michelle Isaacs, Mariëtte Malherbe, Winél Mans, Jeremy Nuttall, Marisa Russell, Smangaliso Ntshele, Marlie Smit, Leonard Nichiren Solai, Patrick Spence, John Steytler, Kathleen Marie Windle, Maarten Borremans, Sophie Resseler, Jens Van Roey, Wim Parys, Tony Vangeneugden, Ben Van Baelen, Zeda Rosenberg

Bibliographic record

VenueNew England Journal of Medicine · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsMedicineSeroconversionHazard ratioPlaceboConfidence intervalVaginal ringIncidence (geometry)GynecologyObstetricsInternal medicineHuman immunodeficiency virus (HIV)PopulationFamily planningImmunology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized triallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.292
Teacher spread0.277 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designRandomized trial · Other design
Domainnot available
GenreEmpirical

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

Citations467
Published2016
Admission routes1
Has abstractyes

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