Bibliographic record
Abstract
Axial involvement is the hallmark of ankylosing spondylitis (AS), and it is unique in many ways among inflammatory arthritides. By its very anatomical location, it is difficult to assess clinically. Laboratory investigations including inflammatory markers are often unrevealing, and simple imaging such as radiographs remain normal for several years after the onset of the disease and change very slowly — if at all — later in the disease course1. Unlike their efficacy in other inflammatory arthritides, traditional disease-modifying antirheumatic drugs (DMARD) have been ineffective in improving function or reducing signs and symptoms of spinal involvement in AS. The significant efficacy of anti-tumor necrosis factor (TNF) agents in axial disease of AS is therefore even more striking2–5. With the limited therapeutic armamentarium for the management of spinal disease in AS (e.g., physical therapy, nonsteroidal antiinflammatory drugs), the use of anti-TNF agents is likely to grow, although the biggest hurdle remains their cost. A systematic review along with an economic evaluation of the use of the original 3 anti-TNF agents approved for the treatment of AS (etanercept, adalimumab, and infliximab) by the National Institute of Clinical Excellence (NICE) of Britain showed that the incremental cost-effectiveness ratios (ICER) of etanercept and adalimumab were roughly similar, falling below the conventional £30,000 (US $50,000) threshold per quality-adjusted life-year (QALY). However, the ICER for infliximab (IFX) used in the “approved” dose of 5 mg/kg every 6 weeks was in the …
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.291 | 0.075 |
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".