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Record W4300126253 · doi:10.17615/9njc-7b37

Predictive Accuracy of the Veterans Aging Cohort Study Index for Mortality With HIV Infection: A North American Cross Cohort Analysis

2020· article· en· W4300126253 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUNC Libraries · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteNational Institute on AgingDeutsches KrebsforschungszentrumNational Institute on Alcohol Abuse and AlcoholismNational Institutes of HealthCanadian Institutes of Health ResearchCenters for Disease Control and Prevention
KeywordsCohortHuman immunodeficiency virus (HIV)MedicineCohort studyGerontologyDemographyIndex (typography)Environmental healthInternal medicineVirologyComputer science

Abstract

fetched live from OpenAlex

By supplementing an index composed of HIV biomarkers and age (Restricted Index) with measures of organ injury, the Veterans Aging Cohort Study (VACS) Index more completely reflects risk of mortality. We compare the accuracy of the VACS and Restricted Indices 1) among subjects outside the Veterans Healthcare System (VA), 2) over 1–5 years of prior exposure to antiretroviral therapy (ART), and 3) within important patient subgroups.

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.

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 score0.010
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.025
GPT teacher head0.320
Teacher spread0.296 · 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