Expanding the Assessment of Overall Functioning and Health Status in Patients With Spondyloarthritis
Bibliographic record
Abstract
The assessment of disease impact for rheumatological conditions is a challenging topic of relevant interest in the last years. Severity is closely related to disease impact, and related to several aspects of clinical conditions, including, among others, disease activity, physical function, and damage. All these are closely interrelated with the term “quality of life,” reflecting the impact that the disease may have on the patient. The field of spondyloarthritis (SpA) has not been unaware of these concepts, and efforts have been made to develop instruments assessing domains going beyond physical function, disease activity, and pain. Axial SpA (axSpA) is characterized by inflammation and new bone formation affecting the axial skeleton and joints.1 These patients may have symptoms related not only to chronic back pain but also to spinal stiffness, peripheral manifestations, and extramusculoskeletal features. The disease course is characterized by functional disability and limitation in activities and social participation. The influence of the disease on health-related quality of life has been characterized and does not differ in terms of health status, disease activity, and physical function between radiographic and nonradiographic axSpA.2 Considering the variable evolution of axSpA, the assessment of health and functioning is now widely recognized as a relevant outcome … Address correspondence to Dr. W. Bautista-Molano, Rheumatology Department, University Hospital Fundación Santa Fe de Bogota, School of Medicine Universidad El Bosque, Carrera 7 Bis No. 124-56, Office #609, Bogota 111156, Colombia. Email: wilson.bautista{at}gmail.com.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".