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Record W2126010778 · doi:10.1177/1759720x11436240

Imaging in ankylosing spondylitis

2012· article· en· W2126010778 on OpenAlexaff
Mikkel Østergaard, R. Lambert

Bibliographic record

VenueTherapeutic Advances in Musculoskeletal Disease · 2012
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineAnkylosing spondylitisGold standard (test)RadiographyMagnetic resonance imagingRadiologyConventional radiographyEnthesitisSacroiliac jointClinical PracticeDiseaseMedical physicsSurgeryPsoriatic arthritisPhysical therapyPathology

Abstract

fetched live from OpenAlex

Imaging is an integral part of the management of patients with ankylosing spondylitis and axial spondyloarthritis. Characteristic radiographic and/or magnetic resonance imaging (MRI) findings are key in the diagnosis. Radiography and MRI are also useful in monitoring the disease. Radiography is the conventional, albeit quite insensitive, gold standard method for assessment of structural damage in spine and sacroiliac joints, whereas MRI has gained a decisive role in monitoring disease activity in clinical trials and practice. MRI may also, if ongoing research demonstrates a sufficient reliability and sensitivity to change, become a new standard method for assessment of structural damage. Ultrasonography allows visualization of peripheral arthritis and enthesitis, but has no role in the assessment of axial manifestations. Computed tomography is a sensitive method for assessment of structural changes in the spine and sacroiliac joints, but its clinical utility is limited due to its use of ionizing radiation and lack of ability to assess the soft tissues. It is exciting that with continued dedicated research and the rapid technical development it is likely that even larger improvements in the use of imaging may occur in the decade to come, for the benefit of our patients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.228
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.323
Teacher spread0.311 · 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.

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

Citations75
Published2012
Admission routes1
Has abstractyes

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