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Preventing constipation: a review of the laxative potential of food ingredients

2012· review· en· W2017153978 on OpenAlexaff
Pierre Gélinas

Bibliographic record

VenueInternational Journal of Food Science & Technology · 2012
Typereview
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsPsylliumLaxativeConstipationMedicinePopulationDietary fibreEnvironmental healthDietary fiberFood scienceSurgeryBiology

Abstract

fetched live from OpenAlex

Summary Constipation is a highly prevalent and difficult‐to‐cure health problem, forcing 10–20% of the worldwide population to seek medical care. Efficacy of treatments varies greatly among individuals, and problems are becoming more frequent despite higher consumption of fibre‐rich foods, the most popular solution for preventing such gastrointestinal disorders. The evidence that consumption of fibre prevents and relieves constipation is unconvincing or uncertain. The food industry has made great efforts to develop fibre‐rich ingredients, especially those from food by‐products and wastes. Except for psyllium and wheat bran, most of these ingredients have intermediate or low laxative potential and their efficacy needs to be confirmed by more clinical studies. This review suggests that there are major discrepancies between the proposed fibre‐enriched ingredients and the consumers' needs. As a lasting solution to prevent constipation, the true impact of dietary fibre and potent food‐grade laxatives might also be limited by overeating.

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)0.001
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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.049
GPT teacher head0.346
Teacher spread0.297 · 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

Citations26
Published2012
Admission routes1
Has abstractyes

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