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Record W2008833118 · doi:10.3171/2014.9.spine131075

Metastatic renal cell carcinoma mimicking a schwannoma in a dorsal root ganglion: case report

2015· article· en· W2008833118 on OpenAlexaff
Jason K. Wasserman, Eve C. Tsai, Rafael Glikstein, Gerard H. Jansen

Bibliographic record

VenueJournal of Neurosurgery Spine · 2015
Typearticle
Languageen
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineDorsal root ganglionGanglionRenal cell carcinomaSchwannomaPathologyNerve rootMetastasisMetastatic carcinomaAnatomyCarcinomaDorsumCancerInternal medicine

Abstract

fetched live from OpenAlex

Peripheral nerve tumors are soft-tissue tumors that can occur in any nerve throughout the body. The majority of peripheral nerve tumors arise from elements of the nerve sheath with the two most common being neurofibromas and schwannomas. More than 90% of all peripheral nerve tumors are benign. When there is peripheral nerve involvement in metastatic carcinoma, it is often via contiguous spread from the primary mass; hematogenous seeding to a peripheral nerve is seldom seen. In this report the authors describe the even rarer case of metastatic renal cell carcinoma mimicking a schwannoma in a dorsal root ganglion. Cases from the literature show the rarity of this finding and its late clinical appearance. Given that survival in patients with metastatic carcinoma continues to increase, dorsal root ganglion metastasis may become more common over time.

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)0.005
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 score0.009
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0040.003
Scholarly communication0.0030.003
Open science0.0030.003
Research integrity0.0090.005
Insufficient payload (model declined to judge)0.0040.003

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 head0.049
GPT teacher head0.289
Teacher spread0.239 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

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