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Record W2080267731 · doi:10.3899/jrheum.090274

Tumoral Calcinosis of Thoracic Spine Associated with Systemic Sclerosis: Figure 1.

2009· article· en· W2080267731 on OpenAlexvenueno aff
Takehiko Ogawa, Takehisa Ogura, Norihide Hayashi, Ayako Hirata

Bibliographic record

VenueThe Journal of Rheumatology · 2009
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging and Pathology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCalcinosisSclerodactylyTelangiectasiaTrunkScleroderma (fungus)WeaknessNeurological examinationCalcificationPhysical examinationAnkylosing spondylitisSoft tissueSurgeryRadiologyPathology

Abstract

fetched live from OpenAlex

Soft-tissue calcinosis is a common manifestation in patients with systemic sclerosis (SSc), most typically seen as subcutaneous and intracutaneous calcium deposition in the extremities. By contrast, spinal calcinosis has been the subject of only limited reports1–8. We describe a woman with the diffuse cutaneous form of SSc who presented with serious neurological symptoms, including a rapidly progressive course of motor and sensory disturbance. Computed tomography (CT) of her thoracic spine showed massive intraspinal calcinosis and paraspinal calcinosis causing spinal cord compression. A 53-year-old woman, diagnosed 10 years previously as having the diffuse cutaneous form of SSc, was admitted to our hospital with a 2-week history of rapidly increasing weakness and numbness of her bilateral lower extremities. She had daily episodes of Raynaud’s phenomenon, esophageal hypomotility, and interstitial lung disease. On admission, physical examination revealed skin thickening over the trunk, face and limbs, multiple ulcerations of her fingertips, peripheral calcinosis cutis, and telangiectasia. Neurologic examination revealed severe weakness in her bilateral lower extremities …

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 score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0170.004

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 head0.031
GPT teacher head0.303
Teacher spread0.271 · 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

Citations16
Published2009
Admission routes1
Has abstractyes

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