Mixed Crystal Disease: A Tale of 2 Crystals
Bibliographic record
Abstract
A report published in this issue of The Journal estimated the recurrence rate of acute calcium pyrophosphate (CPP) crystal arthritis and its associated factors1 on 111 patients with a first acute flare of CPP arthritis. Of these, 13 were considered to have gout on top of fulfilling the study’s definition of acute CPP crystal arthritis: 1 had monosodium urate (MSU) crystals documented on a different occasion in a different joint, 1 had simultaneous observation of MSU and CPP crystals in the same joint, 7 had prior podagra, and 4 had been diagnosed with gout based on elevated uric acid and synovitis in a joint different from that in which CPP arthritis was diagnosed. At the very least, the patient with both crystal types in the same joint – and likely some of the others – could be classified as having mixed crystal disease. Aside from occasional data, little is known about this condition. The formation of MSU crystals is a consequence of hyperuricemia, and at least some of the mechanisms of crystal formation appear similar to those of biomineralization2; other factors likely influence the nucleation of the crystals3. At the joint, MSU crystals form on the surface of the joint cartilage and their passage to and … Address correspondence to Prof. E. Pascual, Universidad Miguel Hernandez, Carretera Nacional 332 s/n, 03550, San Juan de Alicante, Alicante, Spain. E-mail: pascual_eli{at}gva.es
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".