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Record W4400792313 · doi:10.3389/fnut.2024.1400719

Determining amino acid requirements in humans

2024· review· en· W4400792313 on OpenAlexaff
Alyssa Paoletti, Glenda Courtney‐Martin, Rajavel Elango

Bibliographic record

VenueFrontiers in Nutrition · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of British ColumbiaBC Children's HospitalUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsAmino acidAmino acid analysisBiochemistryBiology

Abstract

fetched live from OpenAlex

Amino acids form the building blocks of body protein. Dietary protein sources provide the amino acids needed, but protein sources vary widely in amio acid composition. To ensure humans can meet body demands for amino acids, amino acid intake recommendations are provided by the Dietary Reference Intakes (DRI) and by Food and Agriculture Organization/World Health Organization/United Nations University (FAO/WHO/UNU). Current amino acid intake recommendations, however, are based on data collected predominantly from young adult males. The development of the minimally invasive indicator amino acid oxidation (IAAO) method has permitted the evaluation of amino acid requirements in various vulnerable populations. The purpose of this review is to discuss recent amino acid requirement studies in school-age children, pregnant females and the elderly determined using the IAAO technique. These requirements will help to inform evidence-based recommendations that will help to guide dietary guidelines.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.036
GPT teacher head0.329
Teacher spread0.293 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations25
Published2024
Admission routes1
Has abstractyes

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