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Functional Development of Human Fetal Gastrointestinal Tract

2009· article· en· W140430483 on OpenAlexaff
Émile Lévy, Edgard Delvin, Daniel Ménard, Jean‐François Beaulieu

Bibliographic record

VenueMethods in molecular biology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDigestive system and related health
Canadian institutionsUniversité de SherbrookeUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsBiologyGastrointestinal tractComputational biologyCell biologyBioinformaticsBiochemistry

Abstract

fetched live from OpenAlex

The morphological development of the gastrointestinal tract (GI), in laboratory animals as well as in humans, has been well described since more than 100 years. However, even though its functional development and regulatory mechanisms are pretty well understood, our knowledge of the human GI functions originated primarily from studies on rat and mouse. Because of clear differences in genetic make up, development rates and sequences, as well as physiological differences, extrapolations of animal data to the human must be made with caution. A reliable organ culture technique in which the morphological as well as physiological parameters are well maintained has been set up. This technique allows studies of basic physiological functions such as gene expression, localization of specific cell markers, numerous digestive enzymatic activities, and lipid and lipoprotein processing. Furthermore, it also permits to determine and characterize the biological actions of potential regulators such as growth factors and hormones. Finally, the establishment of human intestinal epithelial cell lines allows the validation and the characterization of the molecular mechanisms involved in the specific regulatory pathways of the human GI development.

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: Methods · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.003

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 head0.030
GPT teacher head0.390
Teacher spread0.360 · 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
GenreMethods

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

Citations19
Published2009
Admission routes1
Has abstractyes

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