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Record W2020409290 · doi:10.3899/jrheum.141537

Summary of Sensitivity and Specificity for Psoriatic Arthritis in a South African Cohort according to Classification Criteria

2015· article· en· W2020409290 on OpenAlexvenueno aff
Ajesh B. Maharaj, Jayandran Govender, Kasthurba Maharaj, Michelle Rajkaran, Paul P. Tak

Bibliographic record

VenueThe Journal of Rheumatology · 2015
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsoriatic arthritisCohortInternal medicineArthritisCohort studyDermatology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the sensitivity and specificity of the classification criteria for psoriatic arthritis (PsA) in a South African cohort. METHODS: Data from consecutive patients with PsA and other chronic inflammatory arthritides were collected prospectively. Subjects were classified according to the classification criteria. The sensitivity and specificity in each group of patients were compared with a clinical diagnosis made by a rheumatologist. RESULTS: The European Spondylarthropathy Study Group criteria exhibited the lowest sensitivity followed by the Moll and Wright criteria. The sensitivity and specificity of the ClASsification for Psoriatic ARthritis (CASPAR) criteria were 98.4% and 99.7%, respectively. CONCLUSION: The CASPAR criteria were evaluated in our cohort and they performed well.

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)0.004
metaresearch head score (Gemma)0.014
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.300
Teacher spread0.257 · 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

Citations6
Published2015
Admission routes1
Has abstractyes

Explore more

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