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Record W2742822962 · doi:10.1093/ecco-jcc/jjx109

Research Gaps in Diet and Nutrition in Inflammatory Bowel Disease. A Topical Review by D-ECCO Working Group [Dietitians of ECCO]

2017· review· en· W2742822962 on OpenAlexaff
Rotem Sigall Boneh, Arie Levine, Miranda Lomer, Nicolette Wierdsma, Philip Allan, Gionata Fiorino, Simona Gatti, Daisy Jonkers, Jarosław Kierkuś, Konstantinos H. Katsanos, Silvia Melgar, Elif Sarıtaş Yüksel, Kevin Whelan, Eytan Wine, Konstantinos Gerasimidis

Bibliographic record

VenueJournal of Crohn s and Colitis · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineMedical nutrition therapyInflammatory bowel diseaseEtiologyDiseaseIntensive care medicineCrohn's diseaseInternal medicine

Abstract

fetched live from OpenAlex

Although the current doctrine of IBD pathogenesis proposes an interaction between environmental factors and gut microbiota in genetically susceptible individuals, dietary exposures have attracted recent interest and are, at least in part, likely to explain the rapid rise in disease incidence and prevalence. The D-ECCO working group along with other ECCO experts with expertise in nutrition, microbiology, physiology, and medicine reviewed the evidence investigating the role of diet and nutritional therapy in the onset, perpetuation, and management of IBD. A narrative topical review is presented where evidence pertinent to the topic is summarised collectively under three main thematic domains: i] the role of diet as an environmental factor in IBD aetiology; ii] the role of diet as induction and maintenance therapy in IBD; and iii] assessment of nutritional status and supportive nutritional therapy in IBD. A summary of research gaps for each of these thematic domains is proposed, which is anticipated to be agenda-setting for future research in the area of diet and nutrition in IBD.

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 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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
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 head0.035
GPT teacher head0.350
Teacher spread0.315 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations111
Published2017
Admission routes1
Has abstractyes

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