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Record W4417297714 · doi:10.1002/jgh3.70309

Cronkhite–Canada Syndrome With Multiple Mesenteric Lymphadenopathy: A Case Report

2025· article· en· W4417297714 on OpenAlexaboutno aff
Takashi Nishino, Chikamasa Ichita, Akiko Sasaki, Chihiro Sumida

Bibliographic record

VenueJGH Open · 2025
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical examinationPresentation (obstetrics)Lymph nodeDiarrheaAbdominal computed tomographyPrednisoloneStomach

Abstract

fetched live from OpenAlex

Cronkhite-Canada syndrome (CCS) is a rare nonhereditary disorder characterized by multiple gastrointestinal polyps and ectodermal changes. The mortality rate can reach up to 50% in patients with delayed diagnosis or inadequate treatment. A 78-year-old Japanese woman presented with diarrhea as the primary complaint. Her clinical presentation included diarrhea, dysgeusia, anorexia, and weight loss. Physical examination revealed alopecia, nail atrophy, and hyperpigmentation. Abdominal computed tomography (CT) revealed multiple enlarged mesenteric lymph nodes, whereas endoscopic examination showed numerous hyperplastic polyps extending from the stomach to the colon. Following the diagnosis of CCS, the patient was treated with prednisolone (30 mg/day). Abdominal CT imaging one month later showed a reduction in the mesenteric lymph node size. Although it is uncommon, mesenteric lymphadenopathy can appear in CCS and may regress with corticosteroid therapy.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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 designCase report
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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