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Record W2776463654 · doi:10.1097/md.0000000000009355

Solitary fibrous tumor of the ilium

2017· article· en· W2776463654 on OpenAlexaff
Xiuhong Ge, Jin-Sheng Liao, Ryan Choo, Juncheng Yan, Jingfeng Zhang

Bibliographic record

VenueMedicine · 2017
Typearticle
Languageen
FieldMedicine
TopicSoft tissue tumor case studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineSolitary fibrous tumorAnatomyCell biology

Abstract

fetched live from OpenAlex

RATIONALE: Solitary fibrous tumors (SFTs) are rare spindle cell tumors that are most commonly found in the mediastinal pleura. Although there are increasingly more reports of extra-pleural SFTs, reports of SFTs in bone are very rare. To our knowledge, a SFT of the ilium has not yet been reported. With low specificity on computer tomograpy and magnetic resonance imaging, SFTs are easily misdiagnosed. PATIENT CONCERNS: A 33-year-old man visited our hospital due to repeated right ilium pain for 3 months. The pain was dull and bearable, with no hip joint dyskinesia. The relevant physical examinations are negative. The patient was healthy before and had a negative family history. Radiologically, a large mass with inhomogeneous attenuation and intensity and obvious heterogeneous enhancement was misdiagnosed as a giant cell tumor of ilium. DIAGNOSES: The man was diagnosed as the solitary fibrous tumor of right ilium. INTERVENTIONS: The patient was performed an "incision biopsy of the right ilium" and "extended resection of tumor". OUTCOMES: The pathology and immunohistochemistry was confirmed as the solitary fibrous tumors. The patient was followed-up by computed tomography of pelvis in local hospital every 6 mouths, and there is no recurrence and any symptoms. LESSONS: We learned that the solitary fibrous tumor could locate in the ilium, and when we see imaging manifestations like this case, we should think it may be SFT.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.324
Teacher spread0.292 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2017
Admission routes1
Has abstractyes

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