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Record W1595640160

Providing Meals for Athletic Groups

2006· book-chapter· en· W1595640160 on OpenAlexaboutno aff
Nicola K. Cummings, Ruth Crawford, Michelle Cort, Fiona Pelly

Bibliographic record

VenueUSC Research Bank (University of the Sunshine Coast) · 2006
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsDieticiansAthletesSports nutritionSports medicinePosition statementMedical educationFemale athlete triadMedicineFamily medicinePhysical therapyEating disorders
DOInot available

Abstract

fetched live from OpenAlex

This text contains nutrition information, coupled with advice on how to apply sports nutrition guidelines in a clinical or practical framework.Clinical Sports Nutrition is a comprehensive reference that provides state-of-the-art sports nutrition information, coupled with advice on how to apply sports nutrition guidelines in a clinical and practical framework. Each chapter contains specific reviews followed by practice tips. The contributing authors are leading academics, physicians and sports dieticians from Australia, Canada, United States, United Kingdom and Finland. This edition has been revised with an emphasis on updating knowledge and practice that developed since 2000. In particular it provides valuable new information on: female athlete triad and the new ACSM/IOC position statement in 2005, exercise and the immune system, antioxidants and the athlete, food services for athletes and nutrition for travel. [Book Synopsis]

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)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.284
Threshold uncertainty score0.948

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2840.213

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 head0.047
GPT teacher head0.270
Teacher spread0.223 · 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
GenreOther

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

Citations7
Published2006
Admission routes1
Has abstractyes

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