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Record W4283753102 · doi:10.1177/00494755221094167

Clinical guideline utilization in Uganda: A scoping review and comparison

2022· review· en· W4283753102 on OpenAlexaff
Rajan Bola, Raymond Bernard Kihumuro, Joseph Ngonzi, Ronald Lett

Bibliographic record

VenueTropical Doctor · 2022
Typereview
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsCanadian Society for International Health
Fundersnot available
KeywordsMedicineMEDLINEGuidelineDeveloping countryFamily medicineEconomic growthPathologyPolitical science

Abstract

fetched live from OpenAlex

Countries such as Uganda often depend on clinical practice guidelines from developed countries, non-profit charities, and international organizations. The sources and organizations that provide most of the guidelines used in Uganda are not well documented. The primary objective of this article was to determine whether a scoping review of scientific, peer-reviewed literature could identify the clinical guidelines actually used in Uganda. A secondary objective was to examine which organizations provided the majority of guidelines used. We therefore searched for consensus documents, guidelines, and meta-analyses published for use in African countries indexed in PubMed, OVID Medline, and Embase, and then surveyed guidelines currently in use in Ugandan medical practice. We thus compared these two sets of guidelines, as well as their breadth, geography, and sources, to make recommendations for similar low-income countries.

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)0.035
metaresearch head score (Gemma)0.143
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 score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.143
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0320.036
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.705
GPT teacher head0.661
Teacher spread0.044 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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