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Record W2947277319 · doi:10.1089/aid.2019.0074

HIV Research for Prevention 2018: From Research to Impact Conference Summary and Highlights

2019· article· en· W2947277319 on OpenAlexaff
Barbara L. Shacklett, Julià Blanco, Lisa Hightow‐Weidman, Nyaradzo Mgodi, José Alcamı́, Susan Buchbinder, Mike Chirenje, Smritee Dabee, Mamadou Diallo, Kostyantyn Dumchev, Carolina Herrera, Matthew E. Levy, Enrique Martín‐Gayo, Kate M. Mitchell, Kenneth K. Mugwanya, Krishnaveni Reddy, Marta Rodríguez‐García, Chelsea L. Shover, Tripti Shrivastava, Georgia D. Tomaras, Michiel T. van Diepen, Monika Walia, Mitchell Warren, Amapola Manrique, Bargavi Thyagarajan, Tamara Torri

Bibliographic record

VenueAIDS Research and Human Retroviruses · 2019
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversité Laval
FundersCHIST-ERANational Institute of Mental HealthNational Institute on AgingViiV HealthcareBill and Melinda Gates FoundationInstituto de Salud Carlos IIIMerck Sharp and DohmeAgence Nationale de Recherches sur le Sida et les Hépatites ViralesNational Institute of Allergy and Infectious DiseasesMedical Research CouncilSouth African Medical Research CouncilNational Institutes of HealthU.S. Department of Health and Human ServicesInternational AIDS Vaccine InitiativeGilead Sciences
KeywordsHuman immunodeficiency virus (HIV)GlobeMedicinePublic relationsTranslational researchKnowledge translationPolitical scienceMedical educationFamily medicineKnowledge managementComputer sciencePathology

Abstract

fetched live from OpenAlex

The HIV Research for Prevention (HIVR4P) conference is dedicated to advancing HIV prevention research, responding to a growing consensus that effective and durable prevention will require a combination of approaches as well as unprecedented collaboration among scientists, practitioners, and community workers from different fields and geographic areas. The conference theme in 2018, "From Research to Impact," acknowledged an increasing focus on translation of promising research findings into practical, accessible, and affordable HIV prevention options for those who need them worldwide. HIVR4P 2018 was held in Madrid, Spain, on 21-25 October, with >1,400 participants from 52 countries around the globe, representing all aspects of HIV prevention research and implementation. The program included 137 oral and 610 poster presentations. This article presents a brief summary of highlights from the conference. More detailed information, complete abstracts as well as webcasts and daily Rapporteur summaries may be found on the conference website.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.235
GPT teacher head0.509
Teacher spread0.274 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations4
Published2019
Admission routes1
Has abstractyes

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