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Record W2166460610 · doi:10.3945/ajcn.2009.29092

Systematic review to support the development of nutrient reference intake values: challenges and solutions

2010· article· en· W2166460610 on OpenAlexfundno aff
Mei Chung, Ethan M. Balk, Stanley Ip, Jounghee Lee, Teruhiko Terasawa, Gowri Raman, Thomas A Trikalinos, Alice H. Lichtenstein, Joseph Lau

Bibliographic record

VenueAmerican Journal of Clinical Nutrition · 2010
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsnot available
FundersNational Center for Research ResourcesPublic Health AgencyAgency for Healthcare Research and QualityNational Institutes of HealthU.S. Department of Health and Human ServicesPublic Health Agency of CanadaHealth CanadaU.S. Public Health ServiceOffice of Dietary SupplementsU.S. Department of Agriculture
KeywordsSystematic reviewProcess (computing)Transparency (behavior)Management scienceComputer scienceProcess managementMEDLINEPolitical scienceEngineering

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.434
metaresearch head score (Gemma)0.752
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.566
Threshold uncertainty score0.698

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4340.752
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0310.012
Bibliometrics0.0210.021
Science and technology studies0.0020.005
Scholarly communication0.0110.015
Open science0.0140.006
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.122
GPT teacher head0.410
Teacher spread0.288 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designSystematic review
DomainMethods
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

Citations28
Published2010
Admission routes1
Has abstractno

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