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Record W6944244886 · doi:10.17605/osf.io/e3pgz

ENSANUT Ecuador 2018 - Open Data

2021· article· es· W6944244886 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2021
Typearticle
Languagees
FieldEnvironmental Science
TopicPublic Health and Environmental Issues
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPopulationPublic healthGovernment (linguistics)Principal (computer security)Identification (biology)

Abstract

fetched live from OpenAlex

La Encuesta Nacional de Salud y Nutrición del Ecuador – ENSANUT 2018 es una operación estadística por muestreo probabilístico que consta en el Programa Nacional Estadístico con periodicidad quinquenal y cuyo objetivo principal es generar indicadores sobre los principales problemas y la situación de salud de la población ecuatoriana con el fin de evaluar y generar las políticas públicas en temas de salud y nutrición. Titular: Gobierno de la República del Ecuador.

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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesOpen science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.279
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0090.052
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.9260.963

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 head0.042
GPT teacher head0.312
Teacher spread0.270 · 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