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Record W1976204719 · doi:10.5489/cuaj.1452

A unique case of kidney’s collecting system MALT lymphoma

2014· article· en· W1976204719 on OpenAlexvenueno aff
Seyed Alaeddin Asgari, Hamidreza Baghani Aval, Seyed Ali Asgari, Keyvan Kheradmand

Bibliographic record

VenueCanadian Urological Association Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNephrectomyMALT lymphomaKidneyUreterLymphomaPathologyGastrointestinal tractMucosa-associated lymphoid tissueLesionLymphatic systemImmunohistochemistryRadiologyUrologyInternal medicine

Abstract

fetched live from OpenAlex

Low-grade B cell lymphomas of mucosa-associated lymphoid tissue (MALT lymphomas) are mostly seen in the gastrointestinal tract. MALT lymphomas involving kidney are extremely rare. We report on a case of MALT lymphomas of the kidney. A 74-year-old woman presented with an episode of gross hematuria and right flank pain. In renal sonography, we found a hypoecho lesion measuring 61 × 58 × 44 mm in the lower pole of right kidney. A computed tomography scan revealed an enlarged hypodense soft tissue measuring 62 × 42 × 37 mm within the pelvic brim of the right kidney, with extension to the proximal portion of the ipsilateral ureter and engulfed it. The patient underwent a right radical nephrectomy. The pathology specimen indicated a lymphoprolifrative disorder involving the kidney and ureter. To obtain a definitive diagnosis, we used an immunohistochemistry, which confirmed the diagnosis of a MALT lymphoma.

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)0.003
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0030.002
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 head0.011
GPT teacher head0.227
Teacher spread0.217 · 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

Citations9
Published2014
Admission routes1
Has abstractyes

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