Bibliographic record
Abstract
Over the last 20 years, there has been tremendous growth in understanding the multifaceted aspects of gout. These developments in research span the gamut from elucidating mechanisms by which urate crystals trigger cellular inflammation, to an exciting expansion of available therapeutic modalities to manage gout.1,2,3,4,5 Concomitantly, we have learned a great deal regarding the genetic contribution to gout susceptibility, while simultaneously observing an amplification in the epidemiology of gout, including newly appreciated risk factors for incident and prevalent disease. Notably, in the 1960s through the 1990s, the approach to treating gout remained quite constant. For decades, acute attacks of gout were managed with either nonsteroidal antiinflammatory drugs, corticosteroid agents, or colchicine, or with a combination thereof.6,7,8 In fact, these approaches remain applicable today. Allopurinol, an inhibitor of xanthine oxidase, and probenecid, a uricosuric agent, both act to lower serum uric acid to prevent gout recurrence. However, in the first 20 years of this century, several new kids have emerged on the block. A second xanthine oxidase inhibitor (febuxostat) is in hand.3 Further, for those with contraindications to frontline acute agents, several interleukin-1 antagonists (canakinumab, rilonacept, and anakinra) have been studied and are seemingly available for off-label use.5,9 For patients refractory to conventional urate-lowering strategies, an entirely new class of therapy was introduced when a mammalian recombinant uricase conjugated to polyethylene glycol (PEG) was brought to market. This PEGylated uricase, or pegloticase, represents an absolute game changer in the management of patients with severe refractory polyarticular tophaceous gout.4 In addition, another novel drug class that directly inhibits the renal epithelial urate transporter (lesinurad) transiently entered the marketplace. Clearly, the range of gout therapy has expanded substantially. In tandem with major advances in … Address correspondence to Dr. A.C. Gelber, Johns Hopkins University School of Medicine, 5200 Eastern Avenue, Mason F. Lord Bldg, Center Tower, Suite 4100, Baltimore, MD 21224, USA. Email: agelber{at}jhmi.edu.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.093 | 0.024 |
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".