ASAS Health Index as an Addition to Routine Clinical Practice
Bibliographic record
Abstract
To the Editor: We have read with great interest the recent editorial published in The Journal by Dr. Kiltz, et al , referring to the possibility of using the Spondyloarthritis international Society Health Index (ASAS HI) as an all-in-one in the assessment of axial spondyloarthritis (axSpA)1. AxSpA has been evaluated over the years with different tools that have tried to determine the degree of activity [Bath Ankylosing Spondylitis Disease Activity Index (BASDAI)/Ankylosing Spondylitis Disease Activity Score (ASDAS)], functional limitations (Bath Ankylosing Spondylitis Functional Index), mobility restrictions (Bath Ankylosing Spondylitis Metrology Index), structural damage accumulated over time (Bath Ankylosing Spondylitis Radiology Index/modified Stoke Ankylosing Spondylitis Spinal Score), or quality of life (Ankylosing Spondylitis Quality of Life scale) of these patients. Most of these instruments constitute the pillar on which both the results of clinical trials, as well as most clinical and therapeutic decisions taken in clinical routine in this disease, are based on2. However, as Kiltz, et al point out in their editorial, the concept … Address correspondence to Dr. R. Queiro, Rheumatology Division, HUCA, Avenida de Roma s/n, 33011, Oviedo, Asturias, Spain. Email: rubenque7{at}yahoo.es.
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 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 | 0.008 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.013 | 0.016 |
| Insufficient payload (model declined to judge) | 0.008 | 0.007 |
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".