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Record W2889277233 · doi:10.3899/jrheum.180363

Management of Temporomandibular Joint Arthritis in JIA: Tradition-based or Evidence-based?

2018· letter· en· W2889277233 on OpenAlexaffvenue
Peter Stoustrup, Marinka Twilt, Cory M. Resnick

Bibliographic record

VenueThe Journal of Rheumatology · 2018
Typeletter
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineTemporomandibular jointArthritisPhysical therapyDentistryFacial symmetryOrthodonticsInternal medicine

Abstract

fetched live from OpenAlex

Only a decade ago, the temporomandibular joint (TMJ) was referred to as “the forgotten joint in juvenile idiopathic arthritis (JIA)” owing to a lack of clinical and research attention1. More recently, with the finding that TMJ arthritis is seen in a majority of patients with JIA2, an increasing amount of research has focused on this joint. TMJ arthritis may cause pain, impair joint and masticatory function, and affect dentofacial growth, leading to facial asymmetry and bite disturbances. TMJ destruction from arthritis significantly harms oral health and general quality of life3. Despite progress in research, strategies for management of TMJ arthritis are still based primarily on conviction and tradition rather than science. Systemic therapy is frequently ineffective in controlling TMJ disease4. By tradition, local management with intraarticular corticosteroid injection (IACI) is a common backup plan5,6. This has evolved from the decades-long effective use of IACI in management of adult temporomandibular disorder7. In early translation of this technique to children with JIA, it was found to be safe and effective8. IACI improves TMJ/mandibular function and provides pain relief for patients with JIA9. Further study, however, has found that the clinical benefits of IACI usually dissipate within the … Address correspondence to Dr. P. Stoustrup, Vennelyst Blvd. 9-11, 8000 Aarhus C, Denmark. E-mail: pstoustrup{at}odont.au.dk

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.593
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.051
GPT teacher head0.297
Teacher spread0.246 · 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 designNot applicable
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
Published2018
Admission routes2
Has abstractyes

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