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Record W2170016261 · doi:10.1159/000360748

Hydration and Obesity Prevention

2014· article· en· W2170016261 on OpenAlexaff
Jean-Michel Borys, J.C. de Ruyter, Hannah Finch, Pauline Harper, Émile Lévy, Julie Ann Mayer, Pierre J. H. Richard, Hugues Ruault du Plessis, Jacob C. Seidell, Jan Vinck

Bibliographic record

VenueObesity Facts · 2014
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineObesityEnvironmental healthPublic healthChildhood obesityIntervention (counseling)GerontologyOverweightPsychiatryEndocrinologyPathology

Abstract

fetched live from OpenAlex

The easy access to an abundance of sugar-sweetened beverages (SSB) is of major concern now that compelling evidence has linked high intakes of these drinks to childhood obesity. Recently, two independent trials showed increased weight in children consuming SSB compared with a control group who received water or drinks with artificial sweeteners Therefore, the high availability and intense marketing of SSB combined with the high rates of childhood obesity worldwide should raise concern among public health professionals as well as politicians In this article, we elaborate on the evidence for the association between SSB and adverse health effects, and propose a multiple-setting behavioral intervention in the community that promotes water and discourages SSB after breast and/or bottle feeding in children between the ages of 0 and 4 years.

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)0.002
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.263
Teacher spread0.248 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

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