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Record W4381329648 · doi:10.1097/bor.0000000000000950

Challenges in treating juvenile idiopathic arthritis

2023· review· en· W4381329648 on OpenAlexaff
Marinka Twilt, Peter Stoustrup, Dax G. Rumsey

Bibliographic record

VenueCurrent Opinion in Rheumatology · 2023
Typereview
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsStollery Children's HospitalAlberta Children's HospitalUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMedicineArthritisJuvenileMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Juvenile idiopathic arthritis (JIA) diagnosis and classification is currently still based on clinical presentation and general laboratory tests. Some joints such as the temporomandibular joint (TMJ) and sacroiliac (SI) are hard to assess and define as actively inflamed based on clinical examination. This review addresses these difficult to assess joints and provides the latest evidence for diagnosis and treatment. RECENT FINDINGS: Recommendations on clinical examination and radiological examination are available. Recent 2021 ACR recommendations were made for TMJ arthritis and in 2019 for sacroiliitis. SUMMARY: New evidence to guide clinical suspicion and need for further investigations are available for these hard to assess joints. These guidelines will help healthcare providers in diagnosis and treatment assessment.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.249
GPT teacher head0.443
Teacher spread0.194 · 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 designOther design
Domainnot available
GenreReview

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

Citations4
Published2023
Admission routes1
Has abstractyes

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