MétaCan
Menu
Back to cohort

Peer-based interventions for reducing morbidity and mortality in HIV-infected women

2017· article· en· W2133902883 on OpenAlexaff
Marion Doull, Annette M. O’Connor, George A. Wells, Peter Tugwell, Vivian Welch

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2017
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsBruyèreUniversity of OttawaUniversity of British Columbia
Fundersnot available
KeywordsProtocol (science)Psychological interventionHuman immunodeficiency virus (HIV)MedicineFamily medicineAlternative medicineNursingPathology

Abstract

fetched live from OpenAlex

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows: To examine the literature and evidence surrounding peer‐based interventions for HIV positive women to determine: 1. The effectiveness of these strategies in improving the physical, mental and psychosocial health of women. 2. Whether these strategies decrease health inequalities between advantaged and disadvantaged groups. Disadvantage will be defined and evaluated across eight factors summarized by the acronym PROGRESS (see outcomes for further definition).

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)0.024
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.035
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.070
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0080.011
Bibliometrics0.0100.008
Science and technology studies0.0020.001
Scholarly communication0.0040.004
Open science0.0030.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0350.002

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 head0.189
GPT teacher head0.462
Teacher spread0.273 · 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 designSystematic review
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".

Quick stats

Citations11
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCochrane Database of Systematic ReviewsSame topicHIV/AIDS Research and InterventionsFrench-language works237,207