MétaCan
Menu
Back to cohort
Record W2518250007 · doi:10.2217/fvl-2016-0085

Interview With Professor Mark a Wainberg

2016· article· en· W2518250007 on OpenAlexaffabout
Mark A. Wainberg

Bibliographic record

VenueFuture Virology · 2016
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsJewish General HospitalMcGill University
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Library scienceOfficerEditor in chiefMedicinePolitical scienceManagementFamily medicineLaw

Abstract

fetched live from OpenAlex

Dr Mark A Wainberg is Professor of Medicine and Microbiology and Immunology at McGill University (Montreal, Canada) and Director of the McGill University AIDS Centre. He served as President of the International AIDS Society between 1998 and 2000 with responsibilities that included organization of the XIII International Congress on AIDS (Durban, South Africa) in 2000. He was also co-Chair of the XVI International AIDS Conference that took place in Toronto, Canada, in August 2006. He is well known for his initial identification of 3TC as an antiviral drug, in collaboration with BioChem Pharma Inc, in 1989, as well as for multiple contributions to the field of HIV drug resistance. Dr Wainberg now works on efforts to achieve a cure for HIV infection. Among other honors, Dr Wainberg is an Officer of the Order of Canada and a Chevalier in the Legion d'Honneur of France, as well as the recipient of a number of honorary doctorates. Dr Wainberg is an author of over 500 research papers and 100 reviews and commentary articles that have appeared in scientific literature. He is co-Editor-in-Chief of Retrovirology, co-Editor-in-Chief of Journal of the International AIDS Society, and is a member of the editorial committees of multiple other journals. More than 30 students have obtained their PhD degrees under his tutelage.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: none
Teacher disagreement score0.472
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.315
Teacher spread0.297 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueFuture VirologySame topicHIV/AIDS Research and InterventionsFrench-language works237,207