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Record W4412707578 · doi:10.1136/bmjgh-2024-018578

Setting health systems research priorities for Afghanistan: an application of the child health and nutrition research initiative (CHNRI) methodology to set a roadmap to 2030

2025· article· en· W4412707578 on OpenAlexafffund
Sama El Baz, Emily C Keats, Hana Tasic, Robert E. Black, David H. Peters, Najibullah Safi, Hannah Tappis, Kerri Wazny, Nadia Akseer

Bibliographic record

VenueBMJ Global Health · 2025
Typearticle
Languageen
FieldMedicine
TopicLegal, Health, Environmental and COVID-19 Challenges
Canadian institutionsYork UniversityNiagara Health System
FundersChildren's Investment Fund FoundationJohns Hopkins Bloomberg School of Public HealthYork UniversityBill and Melinda Gates FoundationJohns Hopkins UniversityWorld Bank Group
KeywordsSet (abstract data type)Child healthPublic healthPolitical scienceMedicineManagement scienceEnvironmental healthComputer scienceNursingFamily medicineEngineering

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)0.131
metaresearch head score (Gemma)0.085
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.869
Threshold uncertainty score0.691

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1310.085
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0110.011
Science and technology studies0.0060.003
Scholarly communication0.0090.004
Open science0.0040.012
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.290
GPT teacher head0.583
Teacher spread0.293 · 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 designQualitative
DomainMethods
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

Citations7
Published2025
Admission routes2
Has abstractyes

Explore more

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