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Record W3211227310

Interview with Dr. Eric J Arts

2021· article· en· W3211227310 on OpenAlexaffabout
Donika Yakoub, Srijain Shrestha

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHIV/AIDS Impact and Responses
Canadian institutionsWestern University
Fundersnot available
KeywordsThe artsLibrary scienceHuman immunodeficiency virus (HIV)Coronavirus disease 2019 (COVID-19)MedicineManagementSociologyPolitical scienceMedical educationFamily medicineDiseaseInfectious disease (medical specialty)PathologyLaw
DOInot available

Abstract

fetched live from OpenAlex

Dr. Eric J Arts is the co-director of the Global Health Systems spoke of the MMASc program and teaches MICROIMM 3500 – Biological and Social Determinants of Disease, GHS 9020 – Policy and Practice to Improve GHS, and GHS 9030 – Field School in Africa. He is also a Professor in the Microbiology and Immunology department at Western University and a Canada Research Chair in HIV Pathogenesis and Viral Control. Dr. Arts founded his laboratory in 1997 when he was a faculty member at Case Western Reserve University. He then established a satellite laboratory – the Joint Clinical Research Centre in Kampala, Uganda. With collaborators, Dr. Arts and his lab have made significant contributions to our understanding of HIV-1 pathogenesis, evolution, drug resistance, and molecular biology. At Western, Dr. Arts is also the lead at Western’s ImPaKT Facility, a group of interdisciplinary experts that are tackling the science behind COVID-19.

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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.728
Threshold uncertainty score0.999

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)0.0050.002

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 head0.077
GPT teacher head0.251
Teacher spread0.173 · 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
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

Citations0
Published2021
Admission routes2
Has abstractyes

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