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Record W2022636687 · doi:10.1007/s10350-005-0018-8

Staging Intra-Abdominal Desmoid Tumors in Familial Adenomatous Polyposis: A Search for a Uniform Approach to a Troubling Disease

2005· article· en· W2022636687 on OpenAlexaff
James M. Church, Terri Berk, Bruce M. Boman, José G. Guillem, Craig Lynch, Patrick Lynch, Miguel A. Rodrı́guez-Bigas, Larry Rusin, Tom Weber

Bibliographic record

VenueDiseases of the Colon & Rectum · 2005
Typearticle
Languageen
FieldMedicine
TopicSoft tissue tumor case studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineFamilial adenomatous polyposisSurgical oncologyPresentation (obstetrics)FibromatosisDiseaseRadiologySurgeryColorectal cancerInternal medicineCancer

Abstract

fetched live from OpenAlex

INTRODUCTION: Desmoid tumors are a clinical problem in 12 to 15 percent of patients with familial adenomatous polyposis. There is no predictably effective treatment for intra-abdominal desmoid tumors, which sometimes cause significant complications by their effects on the ureters or bowel. The relative rarity and the clinical heterogeneity of intra-abdominal desmoid tumors make randomized studies difficult to do. In this article a staging system is proposed to make multi-institutional studies easier. METHODS: Intra-abdominal desmoid tumors can be staged according to their size, clinical presentation and growth pattern. CONCLUSION: A way of staging intra-abdominal desmoid tumors is proposed to facilitate stratification by disease severity during collaborative studies of various treatments.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.289
Teacher spread0.266 · 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 designObservational
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

Citations95
Published2005
Admission routes1
Has abstractyes

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