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Record W2977244791 · doi:10.1097/iop.0000000000001478

Renal Medullary Carcinoma With Metastasis to the Temporal Fossa and Orbit

2019· article· en· W2977244791 on OpenAlexaff
Ritah Chumdermpadetsuk, Andrea A. Tooley, Kyle J. Godfrey, Brian Krawitz, Neil A. Feldstein, Michael Kazim

Bibliographic record

VenueOphthalmic Plastic and Reconstructive Surgery · 2019
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsColumbia College
Fundersnot available
KeywordsMedicineSickle cell traitMalignancyOrbit (dynamics)Renal cell carcinomaMedullary cavityPathologyKidney diseaseMetastasisRadiologyCancerDiseaseInternal medicine

Abstract

fetched live from OpenAlex

A 22-year-old Hispanic man with sickle cell trait presented with blurred vision, double vision, and pain with OD movement. MRI demonstrated an extra-axial mass centered around the temporal bone with extension into the middle cranial fossa and lateral aspect of the extra-conal right orbit, and mass effect on the lateral rectus muscle. Biopsy of the lesion was consistent with renal medullary carcinoma. CT chest/abdomen/pelvis confirmed a primary tumor in the right kidney. No additional metastases were found. Renal medullary carcinoma is a rare, highly aggressive malignancy, which almost exclusively affects young men of African descent with sickle cell trait or sickle cell disease. The authors present the second confirmed case of renal medullary carcinoma metastatic to the orbit, with ocular symptoms prior the typical presenting symptoms of flank pain and hematuria.Renal medullary carcinoma is a highly aggressive malignancy, most commonly seen in African American patients with sickle cell disease. Involvement of the orbit is rare and visual symptoms may precede systemic diagnosis.

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)0.001
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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