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Record W1986500124 · doi:10.3899/jrheum.140773

Dual-energy Computed Tomography for the Evaluation of Calcinosis in Systemic Sclerosis

2015· article· en· W1986500124 on OpenAlexvenueno aff
Vivien Hsu, Mark Bramwit, Naomi Schlesinger

Bibliographic record

VenueThe Journal of Rheumatology · 2015
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCalcinosisDigital Enhanced Cordless TelecommunicationsSoft tissueRadiographyRadiologyScleroderma (fungus)CalcificationGoutNuclear medicinePathologyInternal medicine

Abstract

fetched live from OpenAlex

Dual-energy computed tomography (DECT) imaging can be useful in the evaluation of scleroderma-related calcinosis (SSc calcinosis) of the hands. We performed DECT scans of the hands of patients with symptomatic SSc calcinosis to better characterize the location and radiographic details of the calcinosis and exclude any monosodium urate (MSU) crystal deposition. DECT is an advanced imaging modality useful for assessing soft tissue MSU deposition attributable to gout and visualization of bone and soft tissue structures such as ligaments and tendons1,2,3. We present here DECT images from …

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.086
GPT teacher head0.310
Teacher spread0.224 · 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 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
Published2015
Admission routes1
Has abstractyes

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Same venueThe Journal of RheumatologySame topicGout, Hyperuricemia, Uric AcidFrench-language works237,207