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Record W2790315343 · doi:10.1093/pch/pxx132

Energy and sports drinks in children and adolescents

2017· article· en· W2790315343 on OpenAlexaff
Catherine Pound, Becky Blair, Dana Boctor, Linda Casey, Jeffrey Critch, Catherine M. Farrell, Manjula Gowrishankar, Jae‐Hong Kim, Daniel Roth, Ana M Sant’Anna, Christopher Tomlinson, Sharon Unger, Patricia D’Onghia, Tanis R. Fenton, Laura N. Haiek, Deborah Hayward, Sarah Lawrence, Jennifer McCrea, Sarah Jane Schwarzenberg

Bibliographic record

VenuePaediatrics & Child Health · 2017
Typearticle
Languageen
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsCanadian Paediatric Society
Fundersnot available
KeywordsEnvironmental healthObesityConsumption (sociology)PsychologyAffect (linguistics)StimulantMedicinePsychiatry

Abstract

fetched live from OpenAlex

Sports drinks and caffeinated energy drinks (CEDs) are commonly consumed by youth. Both sports drinks and CEDs pose potential risks for the health of children and adolescents and may contribute to obesity. Sports drinks are generally unnecessary for children engaged in routine or play-based physical activity. CEDs may affect children and adolescents more than adults because they weigh less and thus experience greater exposure to stimulant ingredients per kilogram of body weight. Paediatricians need to recognize and educate patients and families on the differences between sport drinks and CEDs. Screening for the consumption of CEDs, especially when mixed with alcohol, should be done routinely. The combination of CEDs and alcohol may be a marker for higher risk of substance use or abuse and for other health-compromising behaviours.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.300
Teacher spread0.289 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations42
Published2017
Admission routes1
Has abstractyes

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