Bibliographic record
Abstract
During a gathering of the United States & Canadian Academy of Pathology in March 2019, where we celebrated the publication of a new edition of a book on renal histology, a discussion about “TMA” arose. Surya V. Seshan of Weill Cornell Medicine, New York, described a case she recently encountered with the words “Tell Me About It!” And Bob Colvin of Massachusetts General Hospital/Harvard Medical School interrupted: “Yes, that’s TMA — tell me about it!” In this issue of The Journal , Li, et al 1 report on thrombotic microangiopathy (TMA) in lupus nephritis, which is, as the authors state, a relatively uncommon pathological finding in lupus nephritis. Its clinical significance remains to be defined. In their study, TMA was present in 24 (3.5%) of 677 biopsy-proven lupus nephritis cases. Previous studies have also found that TMA is a relatively uncommon finding in lupus nephritis, with a prevalence usually below 10%, although some studies report TMA to be present in up to 25% of renal biopsies with lupus nephritis2. The reported variability of TMA in lupus nephritis may depend on numerous factors including the clinical investigation of patients with systemic lupus erythematosus (SLE), their (genetic) background or geography, but also with the way in which TMA was tested for and evaluated. All histological findings in the study by Li, et al were reevaluated, which led to exclusion of 2 cases in which the histology did not show convincing evidence of renal TMA; by reevaluation no additional cases with TMA were identified. Definitions for TMA vary considerably (in lupus nephritis as well as in other conditions), and careful reevaluation of renal biopsies — not only those with lupus nephritis but also with other diseases — may reveal more or fewer TMA lesions than were initially appreciated. Li, et al … Address correspondence to Dr. I.M. Bajema, Department of Pathology, Leiden University Medical Center, L1-Q, PO Box 9600, 2300 RC Leiden, the Netherlands. E-mail: i.bajema{at}lumc.nl
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.024 | 0.018 |
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".