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Record W1897689975

Suppléments de zinc pour la gastroentérite aiguë.

2013· article· fr· W1897689975 on OpenAlexaboutno aff
Ran D. Goldman

Bibliographic record

VenueEurope PMC (PubMed Central) · 2013
Typearticle
Languagefr
FieldNursing
TopicTrace Elements in Health
Canadian institutionsnot available
Fundersnot available
KeywordsGynecologyZincPolitical scienceHumanitiesMedicineChemistryArt
DOInot available

Abstract

fetched live from OpenAlex

Question La gastroentérite accompagnée de diarrhée est un problème fréquent chez les enfants et peut entraîner une déshydratation, de la morbidité et, dans certains pays, une mortalité importantes. Y a-t-il lieu de donner des suppléments de zinc dans de tels cas? Réponse Le zinc se retrouve dans divers aliments et, au Canada, certains sont enrichis de zinc. Les suppléments de zinc sont éprouvés comme étant une mesure sûre et efficace pour raccourcir la durée des maladies accompagnées de diarrhée et possiblement réduire d’autres complications, dont la mort. Quoique l’Organisation mondiale de la Santé recommande une dose quotidienne de zinc pendant 10 à 14 jours pour prendre en charge la diarrhée aiguë chez l’enfant, les enfants canadiens qui s’alimentent normalement n’ont pas besoin de tels suppléments.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.017
GPT teacher head0.254
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
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

Citations0
Published2013
Admission routes1
Has abstractyes

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Same venueEurope PMC (PubMed Central)Same topicTrace Elements in HealthFrench-language works237,207