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Record W2128337644 · doi:10.4021/wjon222w

Renal Medullary Carcinoma is a Diagnosis Worth Considering: Case Report

2010· article· en· W2128337644 on OpenAlexvenueno aff
Christopher Thomas

Bibliographic record

VenueWorld Journal of Oncology · 2010
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSickle cell traitMedullary cavityLymph nodeBiopsyKidneyRenal cell carcinomaRadiologyPathologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Medullary Renal Carcinoma is a rare, highly malignant neoplasm that originates in the renal medulla and typically affects young black patients with sickle cell trait. We report the case of a 17-year-old boy with a symptomatic left renal tumour. CT revealed that the mass originated from the kidney and was associated with a large para-aortic lymph node mass. Hemoglobin electrophoresis showed sickle cell trait and a needle biopsy confirmed the diagnosis of Renal Medullary Carcinoma. We discuss the obscurity and implications of such a diagnosis. It is essential that clinicians are aware of this diagnosis as any delay can be fatal in the outcome of this highly aggressive and extremely rare cancer.

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)0.006
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 score0.010
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0030.004
Open science0.0020.002
Research integrity0.0100.004
Insufficient payload (model declined to judge)0.0040.002

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 head0.038
GPT teacher head0.320
Teacher spread0.281 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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