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Record W4205993830 · doi:10.1079/cabireviews202217004

Application of metabolomics to assess the intestinal response to dietary supplementation

2022· article· en· W4205993830 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

VenueCABI Reviews · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMetabolomicsBiologyFeed additiveBiotechnologyIdentification (biology)Computational biologyPhysiologyBioinformaticsFood science

Abstract

fetched live from OpenAlex

Abstract Recently, there has been increasing interest in the use of feed supplements for improving human and animal nutrition and health. Identification of nutrient biomarkers is a top priority to measure the biological and physiological effects of dietary components. Metabolomics is an objective and accurate tool to expand our knowledge of biological systems response to feed supplements by defining intestinal pathways and mechanisms. This review focuses on the impact of feed supplements on the host intestinal system and blood constituents, illustrating systemic changes in metabolic pathways and functionality. From scientific reports dealing with metabolomic data, the paper compiles evidence on feed additive effects on small intestine morphology, nutrient absorption, enzyme regulation and intestinal epithelium, as well as colon microbiota community. The review concentrates on the cellular and molecular functions to demonstrate the possible biological effects of feed supplements on health. The combinations of quantitative metabolomic assays are finding applications not only in animal and human nutritional sciences but also in agricultural, medical, and medicinal research.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.053
GPT teacher head0.364
Teacher spread0.311 · 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