Gathering expert consensus to inform a proposed trial in chronic nonbacterial osteomyelitis (CNO)
Bibliographic record
Abstract
Chronic nonbacterial osteomyelitis (CNO) is an autoinflammatory bone disease that primarily affects children and adolescents. CNO is associated with pain, bone swelling, deformity, and fractures. Its pathophysiology is characterized by increased inflammasome assembly and imbalanced expression of cytokines. Treatment is currently based on personal experience, case series and resulting expert recommendations. Randomized controlled trials (RCTs) have not been initiated because of the rarity of CNO, expired patent protection of some medications, and the absence of agreed outcome measures. An international group of fourteen CNO experts and two patient/parent representatives was assembled to generate consensus to inform and conduct future RCTs. The exercise delivered consensus inclusion and exclusion criteria, patent protected (excludes TNF inhibitors) treatments of immediate interest (biological DMARDs targeting IL-1 and IL-17), primary (improvement of pain; physician global assessment) and secondary endpoints (improved MRI; improved PedCNO score which includes physician and patient global scores) for future RCTs in CNO.
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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 | 0.422 | 0.501 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.007 | 0.011 |
| Research integrity | 0.031 | 0.016 |
| Insufficient payload (model declined to judge) | 0.025 | 0.008 |
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".