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Record W2169492895 · doi:10.1301/002966402320387189

Using the New Dietary Reference Intakes to Assess Diets: A Map to the Maze

2002· review· en· W2169492895 on OpenAlexaffabout
Suzanne P. Murphy, Susan I. Barr, Mary I. Poos

Bibliographic record

VenueNutrition Reviews · 2002
Typereview
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDietary Reference IntakeNutrientEnvironmental healthReference valuesReference Daily IntakePopulationMedicineGerontologyBiologyInternal medicineEcology

Abstract

fetched live from OpenAlex

New Dietary Reference Intakes (DRIs) are being set by the Institute of Medicine, and represent a new way of defining nutrient intake recommendations. For the first time, the recommendations for the United States and Canada allow the calculation of the probability of adequacy for an individual, and the prevalence of inadequacy for a population. In addition, possible excessive consumption of many nutrients can be evaluated. The goal of this review is to provide a practical guide to the proper uses of the new DRIs when assessing intakes.

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)0.026
metaresearch head score (Gemma)0.033
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: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.033
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0070.006
Science and technology studies0.0010.005
Scholarly communication0.0050.016
Open science0.0040.003
Research integrity0.0040.013
Insufficient payload (model declined to judge)0.0040.003

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 head0.495
GPT teacher head0.456
Teacher spread0.039 · 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
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

Citations63
Published2002
Admission routes2
Has abstractyes

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