MétaCan
Menu
Back to cohort
Record W2339142837 · doi:10.1039/c6fo00230g

Designing food delivery systems: challenges related to the in vitro methods employed to determine the fate of bioactives in the gut

2016· review· en· W2339142837 on OpenAlexafffund
Elena Arranz, Milena Corredig, Anilda Guri

Bibliographic record

VenueFood & Function · 2016
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Guelph
FundersCanada Research ChairsDairy Farmers of OntarioUniversity of GuelphFundación Alfonso Martín Escudero
KeywordsIn vitroBiochemical engineeringBiotechnologyComputational biologyBiologyChemistryRisk analysis (engineering)BusinessComputer scienceData scienceEngineeringBiochemistry

Abstract

fetched live from OpenAlex

An in depth understanding of the underpinning mechanisms that relate to food disruption and processing in the gastrointestinal tract is necessary to achieve optimal intake of nutrients and their bioefficacy. Although in vivo trials can provide insights on physiological responses of nutrients, in vitro assays are often applied as tools to understand specific mechanisms, or as prescreening methods to determine the factors associated with the uptake of food components in the gastrointestinal tract. In vitro assays are also often utilized to design novel or improved food delivery systems. In this review the available approaches to study delivery and uptake of food bioactives and the associated challenges are discussed. For an in depth understanding of food processing in the gastrointestinal tract, it is necessary to apply multidisciplinary methodologies, at the interface between materials science, chemistry, physics and biology.

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)0.004
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.163
GPT teacher head0.329
Teacher spread0.166 · 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 teacher head, not a consensus.

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

Citations24
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueFood & FunctionSame topicProteins in Food SystemsFrench-language works237,207