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Record W4224039153 · doi:10.1177/02601060221093430

Does the 2019 Canada’s Food Guide meet the needs of young athletes?

2022· article· en· W4224039153 on OpenAlexaffabout
Alexandra J. Heidl, Kathleen Litzenberger, Tamara R. Cohen, Hugues Plourde

Bibliographic record

VenueNutrition and Health · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsBC Children's HospitalMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsAthletesIndex (typography)MealEnergy requirementGerontologyMedicineEnvironmental healthPsychologyPhysical therapyComputer science

Abstract

fetched live from OpenAlex

Background: The Canada’s Food Guide (CFG) encourages Canadians to consume a balanced plate. However, this recommendation may not meet the nutritional needs of young athletes who have increased nutritional requirements. Aim: To evaluate how the 2019 CGF can be used to meet the nutritional needs of young athletes. Method: Five menu scenarios were created using the CFG’s balanced plate and recipes from Health Canada. Each menu was analyzed to compare nutrient and energy needs of an index athlete (15-year-old male, 71 kg). Estimated energy requirements were based on nutrition guidelines set by National and International sports-nutrition position statements. Results: The adjusted CFG balanced plate plus an energy dense beverage at every meal was the closest to meeting the index athlete’s nutrient requirements. Conclusion: The 2019 CFG’s balanced plate needs to be adjusted to meet the nutritional requirements of individuals with active lifestyles.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.013
GPT teacher head0.255
Teacher spread0.242 · 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 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

Citations3
Published2022
Admission routes2
Has abstractyes

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