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Record W2167516350 · doi:10.3945/ajcn.2008.27154

Opportunities and challenges in conducting systematic reviews to support the development of nutrient reference values: vitamin A as an example

2009· article· en· W2167516350 on OpenAlexaff
Robert M. Russell, Mei Chung, Ethan M. Balk, Stephanie A. Atkinson, Edward L. Giovannucci, Stanley Ip, Alice H. Lichtenstein, Susan T. Mayne, Gowri Raman, A. Catharine Ross, Thomas A Trikalinos, Keith P. West, Joseph Lau

Bibliographic record

VenueAmerican Journal of Clinical Nutrition · 2009
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsMcMaster University
FundersU.S. Department of Health and Human ServicesAgency for Healthcare Research and QualityNational Institutes of HealthU.S. Public Health ServiceOffice of Dietary SupplementsU.S. Department of Agriculture
KeywordsWorkgroupSystematic reviewSet (abstract data type)Process (computing)Medical literatureGovernment (linguistics)Management scienceMEDLINEComputer scienceMedicinePolitical sciencePathologyEngineering

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)0.822
metaresearch head score (Gemma)0.899
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.178
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.8220.899
Meta-epidemiology (narrow)0.0060.006
Meta-epidemiology (broad)0.0220.012
Bibliometrics0.0250.025
Science and technology studies0.0060.014
Scholarly communication0.0230.039
Open science0.0150.014
Research integrity0.0220.019
Insufficient payload (model declined to judge)0.0050.001

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 head0.692
GPT teacher head0.508
Teacher spread0.184 · 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 designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations46
Published2009
Admission routes1
Has abstractno

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