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A rare case of mixed adenoneuroendocrine carcinoma mimicking acute appendicitis

2021· article· en· W3170499597 on OpenAlexaff
Chiara Rinaldo, Roberta Blasio, Michela TANGA, Paola Gagliardi, Dario Grimaldi, Fábio Fernando Elói Pinto

Bibliographic record

VenueJournal of Radiological Review · 2021
Typearticle
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsCentre Casa
Fundersnot available
KeywordsMedicineRadiologyAdenocarcinomaAbdominal painNeuroendocrine differentiationLesionPathologicalAppendicitisPathologyInternal medicineSurgeryCancer

Abstract

fetched live from OpenAlex

Mixed adeno-neuroendocrine carcinoma (MANEC) is an uncommon pathological diagnosis newly acknowledged by the World Health Organization in 2010. MANEC is a neoplasm with significant histological heterogeneity and characterized by the concurrent presence of both adenocarcinomatous and neuroendocrine differentiation. Here, we report the case of a 34-year-old woman presenting to our Emergency Department with severe abdominal pain, peritonism, marked neutrophilia, and anemia. In the suspicion of an acute appendicitis, the patient underwent an abdominal Ultrasound revealing in the right iliac fossa the presence of a hypo-anechoic lesion associated with a hyperechoic appearance of the neighboring perivisceral adipose tissue. Subsequently, a contrast-enhanced abdominal Computed Tomography was performed, showing a polylobed lesion, with peripheral contrast enhancement and hypodense central core, not dissociable from the last ileal loop and from the cecum. Abdominal surgery was then performed: the histological examination on the surgical sample proved a small cell neuroendocrine intestinal carcinoma with well differentiated adenocarcinoma’s areas.

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)0.004
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0040.002
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 head0.043
GPT teacher head0.364
Teacher spread0.321 · 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
Published2021
Admission routes1
Has abstractyes

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