MétaCan
Menu
Back to cohort
Record W2523770807

Public health in crisis-affected populations. A practical guide for decision-makers

2007· article· en· W2523770807 on OpenAlex
Francesco Checchi, Michelle Gayer, RF Grais, Eileen Mills

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMedecins Sans Frontieres Field Research (Medecins Sans Frontieres) · 2007
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsnot available
FundersForeign Affairs and International Trade CanadaOverseas Development InstituteGovernment of Canada
KeywordsPublic healthPolitical scienceMedicinePublic economicsPublic relationsEnvironmental healthEconomicsNursing
DOInot available

Abstract

fetched live from OpenAlex

He has worked for Mdecins Sans Frontires (MSF), Epicentre and the World Health Organisation (WHO) in various conflict-affected countries.Most of his work has been on African sleeping sickness, malaria, health survey methods and epidemiology in crisis-affected populations.Michelle Gayer is a medical officer at the WHO in Geneva, where she develops standards, guidelines and tools, conducts training and provides field assistance on communicable disease surveillance and control in humanitarian emergencies.She has provided technical support to national authorities, UN agencies, NGOs and international organisations in numerous conflict and post-conflict settings and after natural disasters

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.744
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.284
GPT teacher head0.543
Teacher spread0.259 · 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