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Record W2035146728 · doi:10.1093/ofid/ofv036

Effect of Intercurrent Infections and Vaccinations on Immune and Inflammatory Biomarkers Among Human Immunodeficiency Virus-Infected Adults on Suppressive Antiretroviral Therapy

2015· article· en· W2035146728 on OpenAlexafffund
Darrell H. S. Tan, Leah Szadkowski, Janet Raboud, Tae Joon Yi, Brett Shannon, Rupert Kaul, W. Conrad Liles, Sharon Walmsley

Bibliographic record

VenueOpen Forum Infectious Diseases · 2015
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health ResearchOntario HIV Treatment Network
KeywordsMedicineVaccinationImmune systemImmunologyAntiretroviral therapyHuman immunodeficiency virus (HIV)ImmunodeficiencyVirologyVirusViral load

Abstract

fetched live from OpenAlex

We used generalized estimating equations to quantify the impact of recent vaccination or intercurrent infections on immune and inflammatory biomarkers among 144 human immunodeficiency virus (HIV)-infected adults with HIV RNA < 50 copies/mL on antiretroviral therapy. These events were associated with a 2.244 µg/mL increase in high sensitivity C-reactive protein and should be routinely assessed in future studies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.884

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)0.0000.000

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 head0.011
GPT teacher head0.318
Teacher spread0.307 · 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 teacher head, 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

Citations4
Published2015
Admission routes2
Has abstractyes

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