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Record W2154434972 · doi:10.3390/nu6126076

Selected Nutrients and Their Implications for Health and Disease across the Lifespan: A Roadmap

2014· article· en· W2154434972 on OpenAlexaff
Szabolcs Péter, Manfred Eggersdorfer, Dieneke van Asselt, Erik Buskens, Patrick Detzel, Karen Freijer, Berthold Koletzko, Klaus Kraemer, Folkert Kuipers, Lynnette M. Neufeld, Rima Obeid, Simon Wieser, Armin Zittermann, Peter Weber

Bibliographic record

VenueNutrients · 2014
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsNutrition International
FundersDSM Nutritional ProductsUniversitair Medisch Centrum Groningen
KeywordsNutrientDiseaseGerontologyBiologyEnvironmental healthMedicineEcologyInternal medicine

Abstract

fetched live from OpenAlex

Worldwide approximately two billion people have a diet insufficient in micronutrients. Even in the developed world, an increasing number of people consume nutrient-poor food on a regular basis. Recent surveys in Western countries consistently indicate inadequate intake of nutrients such as vitamins and minerals, compared to recommendations. The International Osteoporosis Foundation's (IOF) latest figures show that globally about 88% of the population does not have an optimal vitamin D status. The Lancet's "Global Burden of Disease Study 2010" demonstrates a continued growth in life expectancy for populations around the world; however, the last decade of life is often disabled by the burden of partly preventable health issues. Compelling evidence suggests that improving nutrition protects health, prevents disability, boosts economic productivity and saves lives. Investments to improve nutrition make a positive contribution to long-term national and global health, economic productivity and stability, and societal resilience.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.374
Teacher spread0.338 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
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

Citations36
Published2014
Admission routes1
Has abstractyes

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