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Record W7071861011

Three emerging nutritional problems in populations in vulnerable contexts

2023· article· en· W7071861011 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

VenueMagazine Portal Bibliotech Digital (Universidad Nacional de Colombia) · 2023
Typearticle
Languageen
FieldComputer Science
TopicQR Code Applications and Technologies
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsBreastfeedingVulnerability (computing)Early childhoodBreast feedingWindow of opportunityBreast milkHealth literacyPopulationHealth equity
DOInot available

Abstract

fetched live from OpenAlex

Early childhood is an extremely vulnerable period due to the rapid development of children's brain architecture during those years. It is a window of opportunity to protect children from adverse conditions, considering that health inequities within populations continue to increase. This review presents three emerging problems that contribute to the increase in these inequities in children during early childhood: excessive gestational weight gain (GWG), the vulnerability of mothers to the aggressive marketing of breast milk substitutes industry and health literacy. Strategies in the clinical setting are exposed to taking action: an approach that considers the determinants of health in excessive GWG, be aware of the International Code of Marketing of Breastmilk Substitutes and its impact on the protection of breastfeeding and the universal health literacy precautions. It also highlights the need for holistic approaches and the complementarity of individual and populational approaches to reduce gaps in early childhood health inequities.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.612
Threshold uncertainty score0.919

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.016
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.269
Teacher spread0.236 · 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