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Record W3113795604 · doi:10.14740/jmc3598

Debulking of Advanced Gastrointestinal Stromal Tumor With Peritoneal Carcinomatosis Refractory to Imatinib and Sunitinib: A Case Report

2020· article· en· W3113795604 on OpenAlexvenueno aff
Talia Rave, Manrique Guerrero, Derick Christian, Jamshed Zuberi

Bibliographic record

VenueJournal of Medical Cases · 2020
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Tumor Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSunitinibDebulkingGiSTImatinibStromal tumorTyrosine-kinase inhibitorStromal cellOncologyRefractory (planetary science)Tyrosine kinaseGastrointestinal tractInternal medicineSunitinib malateMetastasisTumor DebulkingSurgeryGastroenterologyChemotherapyCancerOvarian cancerReceptor

Abstract

fetched live from OpenAlex

Gastrointestinal stromal tumors (GISTs) are non-epithelial stromal tumors that arise in the gastrointestinal tract. Pharmacological treatments for GIST are tyrosine kinase inhibitors. For metastatic disease, debulking may be helpful in reducing the tumor burden, thus increasing the effectiveness of tyrosine kinase inhibitors. Debate on whether resection would benefit the patient is still present. Here is a case of a 52-year-old African American male presenting with metastatic malignant GIST with peritoneal carcinomatosis refractory to imatinib and sunitinib. Since this patient had stage IV metastasis it was ultimately decided to proceed with a therapeutic debulking procedure. For this patient, the procedure increased the effectiveness of the medication and reduced mass effect symptoms, improving quality of life.

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 score0.006
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0060.004
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 head0.041
GPT teacher head0.329
Teacher spread0.288 · 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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