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Virologic and Immunologic Response, Clinical Progression, and Highly Active Antiretroviral Therapy Adherence

2002· review· en· W2084787456 on OpenAlex
Natasha Press, Mark Tyndall, Evan Wood, Robert S. Hogg, Julio Montaner

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJAIDS Journal of Acquired Immune Deficiency Syndromes · 2002
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsAIDS VancouverSt. Paul's Hospital
Fundersnot available
KeywordsMedicineViral loadRegimenAntiretroviral therapyImmunologyHuman immunodeficiency virus (HIV)PopulationInternal medicineIntensive care medicineEnvironmental health

Abstract

fetched live from OpenAlex

A growing body of evidence suggests that a high degree of adherence is required to achieve and maintain a successful virologic response both in the short and long term. This holds true despite the definition of adherence or how it is measured. Reported differences in the degree of adherence required are likely due to differences in study design, difficulty measuring patient adherence, patient population studied, and the antiretroviral regimen studied. Virologic suppression and immunologic response often go hand in hand, but the impact of adherence on change in CD4 count tends to be delayed and, therefore, less apparent than the impact on HIV viral load. Degree of adherence has also been shown to be associated with AIDS-related morbidity, mortality, and hospitalizations.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.103
GPT teacher head0.426
Teacher spread0.323 · 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