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Record W3045495709 · doi:10.1093/ofid/ofaa297

“Myocardial inflammatory changes before and after antiretroviral therapy initiation in people with advanced HIV disease”

2020· article· en· W3045495709 on OpenAlexaff
Alicia Menendez, Rommel Flores-Miranda, D Sánchez-Nava, Rodrigo Ortega-Perez, Pablo F. Belaunzarán-Zamudio, Santiago Pérez-Patrigeón, Ayleen Cárdenas-Ochoa, Jorge Oseguera-Moguel, Jaime Galindo-Uribe, Consuelo Orihuela‐Sandoval, Zuilma Y Vazquez-Ortíz, Jorge Vázquez-Lamadrid, Martha Morelos-Guzmán, Sandra Rosales-Uvera, Brenda Crabtree‐Ramírez, Juan Sierra‐Madero

Bibliographic record

VenueOpen Forum Infectious Diseases · 2020
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineCartAntiretroviral therapyObservational studyImmunosuppressionHuman immunodeficiency virus (HIV)Internal medicineMyocarditisDiseasePopulationCohortCardiologyImmunologyViral load

Abstract

fetched live from OpenAlex

Abstract Because high frequency and late presentation of HIV disease in our population, we decided to explore the presence of myocarditis among people with HIV-infection and advanced immunosuppression (less than 200 CD4+ cells/μL), and to describe the inflammatory changes observed after combined antiretroviral therapy (cART) initiation in an observational, longitudinal, prospective cohort performing cardiovascular MRI (cMRI) and doppler trans-thoracic echocardiogram (TTE).

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.272
Teacher spread0.261 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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