A Move Toward Precision: Innovations in Measuring Spinal Mobility in Axial Spondyloarthritis
Bibliographic record
Abstract
The efficacy of therapeutic interventions in axial spondyloarthritis (axSpA), including its more severe subset of ankylosing spondylitis (AS), is measured primarily using variables that reflect inflammatory activity. Most clinical trials have relied on the Assessment of Spondyloarthritis international Society 20 (ASAS20) or ASAS40 response as primary endpoints, whereas the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and particularly the Ankylosing Spondylitis Disease Activity Score, have proven useful for monitoring disease activity longitudinally.1,2 Another important consideration in axSpA is spinal mobility. Reduced spinal mobility is included in the modified New York (mNY) criteria for AS.3 Both inflammation and structural damage compromise mobility in the spine in axSpA.4 A number of tests are available to measure various aspects of spinal mobility, including the well-known Schober test for lumbar flexion.5 The Bath Ankylosing Spondylitis Metrology Index (BASMI) is a validated composite score that includes 5 measurements: cervical rotation, tragus-to-wall distance, lumbar flexion, lumbar lateral flexion, and intermalleolar distance, the latter being a measurement of hip joint integrity.6 However, limited precision and sensitivity to detect change represent challenges for using the BASMI or individual tests of spinal mobility in research.7 No … Address correspondence to Dr. J. Ermann, Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, HBTM, Room 06002P, 60 Fenwood Road, Boston, MA 02115, USA. Email: jermann{at}bwh.harvard.edu.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.190 | 0.183 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".