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Record W2803554130 · doi:10.1111/nyas.13705

The microscopic anatomy of the esophagus including the individual layers, specialized tissues, and unique components and their responses to injury

2018· review· en· W2803554130 on OpenAlexaff
Xuchen Zhang, Deepa T. Patil, Robert D. Odze, Lei Zhao, Mikhail Lisovsky, Maha Guindi, Robert H. Riddell, Andrew M. Bellizzi, Rhonda K. Yantiss, ILKe Nalbantoglu, Henry D. Appelman

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2018
Typereview
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsEsophagusAnatomyStomachPharynxPlexusMedicineMyenteric plexusSphincterPathologyInternal medicineImmunohistochemistry

Abstract

fetched live from OpenAlex

The esophagus, a straight tube that connects the pharynx to the stomach, has the complex architecture common to the rest of the gastrointestinal tract with special differences that relate to its function as a conduit of ingested substances. For instance, it has submucosal glands that are unique and have a specific protective function. It has a squamous lining that exists nowhere else in the gut except the anus and it has a different submucosal nerve plexus when compared to the stomach and intestines. All of the layers of the esophageal wall and the specialized structures including blood and lymphatic vessels and nerves have specific responses to injury. The esophagus also has unique features such as patches of gastric mucosa called inlet patches at the very proximal part and it has a special sphincter mechanism at the most distal aspect. This review covers the normal microscopic anatomy of the esophagus and the patterns of reaction to stress and injury of each layer and each special structure.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.206
GPT teacher head0.443
Teacher spread0.238 · 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

Citations23
Published2018
Admission routes1
Has abstractyes

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