Bibliographic record
Abstract
Of the many things that people with ankylosing spondylitis (AS)/axial spondyloarthritis (axSpA) would like the medical profession to achieve for them, among the most pressing is providing effective ways of managing or preventing flares. Flares present a difficult set of problems: They are not predictable and often occur when contact with a physician or physiotherapist is not possible; and in any event, we can neither define nor measure them. And yet they are a major problem that needs to be tackled. Moreover, whatever they are, effective treatment of axSpA ought to prevent them. In this issue of The Journal , Jacquemin, et al 1 have therefore rightly drawn attention to the issue of flares in axSpA and explored frequency and duration in a group of Canadian patients at a time when few were receiving biologic treatment. Although no definition or description of flare was used, they found that most patients admit to having flares with a mean duration of 2 weeks. Indeed, this and other studies2,3,4 agree that many people with axSpA consider that flares are very common and sometimes virtually continuous. So what is a flare? In rheumatoid arthritis (RA), the term flare implies a periodic increase in symptoms, generally associated with an increase in inflammatory activity, evidenced by clinical signs and a rise in the acute-phase response. In RA, flare can be defined numerically according to validated criteria5. By analogy, it may be assumed that in axSpA a flare also represents a periodic worsening of symptoms associated with an increase in inflammatory activity. However, objective evidence of the latter is not generally available — especially when spinal symptoms are the issue — and a range of other associated problems may cause people with AS to feel worse. The problematic nature of … Address correspondence to Dr. Keat. E-mail: a.keat{at}nhs.net
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".