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Record W7161626472 · doi:10.1136/bmjgh-2025-020891

Prioritising communicable disease research in Afghanistan: an application of the Child Health and Nutrition Research Initiative (CHNRI) methodology

2025· article· en· W7161626472 on OpenAlexaff

Bibliographic record

VenueBMJ Global Health · 2025
Typearticle
Languageen
FieldMedicine
TopicLegal, Health, Environmental and COVID-19 Challenges
Canadian institutionsYork UniversityCanadian Sleep Society
FundersBill and Melinda Gates Foundation
KeywordsCommunicable diseasePublic healthNon-communicable diseaseAfghanPoliomyelitisPoliomyelitis eradicationPsychological interventionPopulationHealth policyHealth services research

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.385
metaresearch head score (Gemma)0.287
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.385
Threshold uncertainty score0.759

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3850.287
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0150.016
Science and technology studies0.0050.004
Scholarly communication0.0070.003
Open science0.0040.011
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.288
GPT teacher head0.576
Teacher spread0.288 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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