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Record W2775641089 · doi:10.1039/c7fo01435j

Dietary fruits and arthritis

2017· review· en· W2775641089 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFood & Function · 2017
Typereview
Languageen
FieldNursing
TopicPomegranate: compositions and health benefits
Canadian institutionsStillwater (Canada)
FundersNational Institute of General Medical SciencesNIH Clinical CenterNational Institutes of Health
KeywordsArthritisMedicinePopulationEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Arthritis is a global health concern affecting a significant proportion of the population and associated with reduced quality of life. Among the different forms of arthritis, osteoarthritis (OA) and rheumatoid arthritis (RA) are the most common and lacking a definite cure in the affected individuals. Fruits, such as berries and pomegranates are rich sources of a variety of dietary bioactive compounds, especially the polyphenolic flavonoids that have been associated with antioxidant, anti-inflammatory and analgesic effects. Emerging research demonstrates a protective role of fruits and their polyphenols in pre-clinical, clinical and epidemiological studies of OA and RA. In this context, commonly available fruits, such as blueberries, raspberries and strawberries, and pomegranates have shown promising results in reducing pain and inflammation in experimental models and in human clinical studies of arthritis. There is also some evidence on the role of specific fruit polyphenols, such as quercetin and citrus flavonoids in alleviating RA symptoms. These emerging data deserve further investigation in rigorous scientific studies to determine the mechanisms, dosing and selection of fruits and fruit extracts in arthritis management.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
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
Bibliometrics0.0000.000
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 head0.179
GPT teacher head0.380
Teacher spread0.202 · 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