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Record W2888526577 · doi:10.2147/jpr.s160660

Second edition of SIMPAR’s “Feed Your Destiny” workshop: the role of lifestyle in improving pain management

2018· review· en· W2888526577 on OpenAlexaff
Manuela De Gregori, Inna Belfer, Roberto De Giorgio, Maurizio Marchesini, Carolina Muscoli, Mariangela Rondanelli, Daniela Martini, Pedro Mena, Laura Isabel Arranz, Silvia Lorente‐Cebrián, Simone Perna, Anna Villarini, Maurizio Salamone, Massimo Allegri, Michael E Schatman

Bibliographic record

VenueJournal of Pain Research · 2018
Typereview
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineDestiny (ISS module)

Abstract

fetched live from OpenAlex

This review is aimed to summarize the latest data regarding pain and nutrition, which have emerged during the second edition of Feed Your Destiny (FYD). Theme presentations and interactive discussions were held at a workshop on March 30, 2017, in Florence, Italy, during the 9th Annual Meeting of Study in Multidisciplinary Pain Research, where an international faculty, including recognized experts in nutrition and pain, reported the scientific evidence on this topic from various perspectives. Presentations were divided into two sections. In the initial sessions, we analyzed the outcome variables and methods of measurement for health claims pertaining to pain proposed under Regulation EC No 1924/2006 of the European Parliament and of the Council of 20 December 2006 on nutrition and health claims made on foods. Moreover, we evaluated how the Mediterranean diet can have a potential impact on pain, gastrointestinal disorders, obesity, cancer, and aging. Second, we discussed the evidence regarding vitamin D as a nutraceutical that may contribute to pain control, evaluating the interindividual variability of pain nature and nurture, and the role of micro-RNAs (miRNAs), polyunsaturated omega 3 fatty acids, and phenolic compounds, with a final revision of the clinical role of nutrition in tailoring pain therapy. The key take-home message provided by the FYD workshop was that a balanced, personalized nutritional regimen might play a role as a synergic strategy that can improve management of chronic pain through a precision medicine approach.

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)0.050
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.910
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0500.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.165
GPT teacher head0.443
Teacher spread0.278 · 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; both teacher heads agree on what is shown here.

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

Citations16
Published2018
Admission routes1
Has abstractyes

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