Comments on the discordant recommendations for the use of symptomatic slow-acting drugs in knee osteoarthritis
Bibliographic record
Abstract
Despite the near concurrent publication by influential scientific organizations, there are important differences in interpretation of the evidence base and the conclusions derived from the recent Osteoarthritis Research Society International (OARSI) guidelines for the management of knee osteoarthritis, the American College of Rheumatology (ACR) guidelines (concerning also hip and hand osteoarthritis) and the algorithm recommendations by the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO). This is particularly evident for the drug class of symptomatic slow-acting drugs in osteoarthritis. In this paper, we highlight these differences and try to understand where they derive from, proposing an evidence-based interpretation.
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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 | 0.051 | 0.279 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.056 | 0.065 |
| Insufficient payload (model declined to judge) | 0.005 | 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".