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Record W2131808131 · doi:10.1016/j.ebiom.2015.07.019

Origins of a Vaccine-Induced, Human Anti-HIV-1 Antibody

2015· article· en· W2131808131 on OpenAlexaff
Jean‐Philippe Julien

Bibliographic record

VenueEBioMedicine · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsVirologyAntibodyHuman immunodeficiency virus (HIV)AIDS VaccinesHIV vaccineMedicineImmunologyVaccine trial

Abstract

fetched live from OpenAlex

A broadly effective HIV-1 vaccine would greatly contribute towards prevention of the 2.1 million new HIV-1 infections estimated to occur annually. Six HIV-1 vaccine efficacy trials in humans have thus far been conducted. Whereas most vaccines showed no efficacy in preventing from HIV-1 infection – and two actually increased infection rates in vaccine recipients – the RV144 Thai phase III HIV-1 vaccine trial is to date the only one to have shown efficacy, albeit marginally (31.2% decrease in HIV-1 acquisition at 42months post-vaccination) (reviewed in (Kim et al., 2015)).

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.037
GPT teacher head0.350
Teacher spread0.313 · 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 designObservational
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

Citations0
Published2015
Admission routes1
Has abstractyes

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