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Record W4281999961 · doi:10.1097/md.0000000000029471

Malignant giant cell tumor of toe

2022· review· en· W4281999961 on OpenAlexaff
Kazuhito Hashimoto, S. Nishimura, Tomohiko Ito, Masao Akagi

Bibliographic record

VenueMedicine · 2022
Typereview
Languageen
FieldMedicine
TopicBone Tumor Diagnosis and Treatments
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsMedicineSoft tissueBiopsyAmputationMagnetic resonance imagingMetastasisSurgical marginGiant cellRadiologyResectionSurgeryPathologyCancerInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: A giant cell tumor of soft tissue (GCST) is a benign soft tissue tumor that often occurs subcutaneously in the extremities. Rare cases of malignant GCST have been reported, but its pathogenesis remains unclear. PATIENTS CONCERNS: We report a case of a 68-year-old man who noticed a painless mass on his second toe one and a half years ago. He visited the Department of Dermatology at our hospital. Magnetic resonance imaging revealed a soft tissue tumor, surrounding the distal aspect of the second toe. DIAGNOSIS: A biopsy of the tumor was performed by a dermatologist, and it revealed a malignant giant cell tumor of the toe. INTERVENTIONS: He was referred to our department and underwent lay amputation for wide-margin resection. OUTCOMES: No recurrence or metastasis was observed 5 years after treatment. CONCLUSION: : Malignant GCST should be treated with wide-margin resection immediately after its 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.080
GPT teacher head0.349
Teacher spread0.269 · 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
Published2022
Admission routes1
Has abstractyes

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