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Record W1494212368 · doi:10.1002/dc.22894

Metastatic small cell osteosarcoma to the liver: A diagnostic pitfall for fine‐needle aspiration cytology

2012· article· en· W1494212368 on OpenAlexaff
Rola H. Ali, Cheng‐Han Lee, Malcolm Hayes

Bibliographic record

VenueDiagnostic Cytopathology · 2012
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsBC Cancer AgencyVancouver General Hospital
Fundersnot available
KeywordsMedicinePathologyFine-needle aspirationRosette (schizont appearance)CytologyBiopsyOsteosarcomaSarcomaMetastatic carcinomaFine needle aspiration cytologyRadiologyCarcinoma

Abstract

fetched live from OpenAlex

We report the fine-needle aspiration cytology of a case of metastatic small cell osteosarcoma to the liver with rosette formation, originating from distal femur, in a 36-year-old female. The aspirate of the liver metastases revealed a relatively monomorphic population of mitotically active small blue round cells arranged in clusters with prominent rosette formation simulating a neuroendocrine carcinoma or other rosette-forming small round cell tumors such as Ewing sarcoma. No extracellular mineralized matrix material was present. Comparison of the liver aspirate with the biopsy from the distal femoral lesion was crucial in reaching the correct diagnosis of metastatic small cell osteosarcoma with rosette formation. This is a potential diagnostic pitfall, particularly if interpreted without the knowledge of a suspected primary bone tumor.

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)0.001
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.034
GPT teacher head0.279
Teacher spread0.246 · 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.

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

Citations10
Published2012
Admission routes1
Has abstractyes

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