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Record W2093120577 · doi:10.1102/1470-7330.2013.0003

Mucinous neoplasms of the appendix: a current comprehensive clinicopathologic and imaging review

2013· review· en· W2093120577 on OpenAlexaff
Sree Harsha Tirumani, Margaret Fraser-Hill, Rebecca C. Auer, Wael Shabana, Cynthia Walsh, Frank Lee, John Ryan

Bibliographic record

VenueCancer Imaging · 2013
Typereview
Languageen
FieldMedicine
TopicIntraperitoneal and Appendiceal Malignancies
Canadian institutionsMcGill UniversityOttawa HospitalMontreal General HospitalUniversity of Ottawa
Fundersnot available
KeywordsPseudomyxoma peritoneiAppendixMedicinePathologyMucinous cystadenomaRadiologyGeneral surgeryOvaryInternal medicine

Abstract

fetched live from OpenAlex

Mucinous neoplasms of the appendix are a heterogeneous group of neoplasms ranging from simple mucoceles to complex pseudomyxoma peritonei. Considerable controversy exists on their pathologic classification and nomenclature. Clear understanding of the histopathologic diversity of these neoplasms helps in establishing proper communication between the radiologist, the pathologist and the surgeon. In this article, we present a brief discussion of the current taxonomy and nomenclature of mucinous neoplasms of the appendix followed by a review of their imaging features. Important points including the significance of identifying extra-appendiceal mucin at imaging, the new classification of pseudomyxoma peritonei into low- and high-grade varieties and the significance of simultaneous ovarian and appendiceal neoplasms are highlighted.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.005
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.076
GPT teacher head0.401
Teacher spread0.325 · 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

Citations148
Published2013
Admission routes1
Has abstractyes

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