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Record W3084265726 · doi:10.1155/2020/2684746

Extraskeletal Myxoid Chondrosarcoma: Long-Term Survival in the Setting of Metastatic Disease

2020· article· en· W3084265726 on OpenAlexaff
Karim Masrouha, Iqbal Multani, Om Bhatt, Michelle Ghert

Bibliographic record

VenueCase Reports in Orthopedics · 2020
Typearticle
Languageen
FieldMedicine
TopicBone Tumor Diagnosis and Treatments
Canadian institutionsMcMaster UniversityHamilton Health SciencesJuravinski Hospital
Fundersnot available
KeywordsMedicineAsymptomaticNatural historyDiseaseQuality of life (healthcare)Intervention (counseling)ChondrosarcomaSurgerySarcomaRadiologyInternal medicinePathology

Abstract

fetched live from OpenAlex

Three cases of extraskeletal myxoid chondrosarcoma (EMC) in patients who presented with pulmonary metastases and were managed with long-term close observation without systemic intervention are presented. Follow-up imaging showed slow progression of their disease over several years, and the patients remained asymptomatic from their pulmonary metastases. This clinical experience provides insight into the natural history of the disease and suggests that some patients may experience long-term survival and remain asymptomatic even without systemic intervention, thereby improving their quality of life by avoiding potentially debilitating treatments.

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)0.002
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.315
Teacher spread0.276 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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