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Record W3036787340 · doi:10.14740/gr1278

Benign Multicystic Peritoneal Mesothelioma Presenting as Appendiceal Abscess: A Diagnostic and Therapeutic Challenge

2020· article· en· W3036787340 on OpenAlexvenueno aff
Charalampos Seretis, Ali Mohamed Elhassan, L Kretzmer, Paul Lim, Anitha Suseelan Menon, Afolabi Awodiya, Subba Rao Kanchustambam

Bibliographic record

VenueGastroenterology Research · 2020
Typearticle
Languageen
FieldMedicine
TopicIntraperitoneal and Appendiceal Malignancies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePeritoneal mesotheliomaMalignancyPerforationAbscessGeneral surgeryTherapeutic approachRadiologySurgeryMesotheliomaDiseasePathology

Abstract

fetched live from OpenAlex

Primary peritoneal tumors are rarely encountered and their management is usually challenging for the clinicians. Especially when the patients with advanced peritoneal malignancy present as surgical emergencies, usually with symptoms of obstruction, perforation or gross space-occupying lesions, the on-call surgical team has to weigh the pros and cons of urgent versus delayed treatment and plans a safe and simultaneously oncologically beneficial therapeutic approach. Herein, we present a case of a Caucasian man who was referred as suspected complicated appendicitis by his primary care physician, with the final diagnosis being benign multicystic mesothelioma. We describe the challenges of the clinical decision making for the emergency general surgeon and relevant diagnostic and therapeutic pitfalls, which can be potentially minimized by early liaison with tertiary units specializing in the treatment of disseminated peritoneal malignancy.

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)0.005
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.070
GPT teacher head0.357
Teacher spread0.287 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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