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Record W2743282227 · doi:10.1016/s2214-109x(17)30253-x

Improving the quality of WHO guidelines over the last decade: progress and challenges

2017· article· en· W2743282227 on OpenAlexaboutno aff
Susan L. Norris, Nathan Ford

Bibliographic record

VenueThe Lancet Global Health · 2017
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsnot available
FundersWorld Health Organization
KeywordsScopusPublic healthGuidelinePolitical scienceMedicinePreparednessGlobal healthPublic relationsMEDLINENursingLaw

Abstract

fetched live from OpenAlex

WHO is a leading and respected source of normative guidance. With a particular focus on the needs of low-income and middle-income countries, the scope of WHO guidelines is vast, ranging from specific interventions aimed at controlling particular aspects of emerging health threats (eg, Infant feeding in areas of Zika virus transmission1) to broad public health guidance (eg, International travel and health2).

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)0.433
metaresearch head score (Gemma)0.719
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.567
Threshold uncertainty score0.699

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4330.719
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0210.027
Science and technology studies0.0050.011
Scholarly communication0.0270.033
Open science0.0180.014
Research integrity0.0140.026
Insufficient payload (model declined to judge)0.0080.004

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 head0.531
GPT teacher head0.607
Teacher spread0.076 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainEvaluation
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

Citations35
Published2017
Admission routes1
Has abstractyes

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