Dr. Kang, <i>et al</i> reply
Bibliographic record
Abstract
We thank Dr. Rothschild for his interest 1 in our article 2 on the incidence of arterial and venous thrombosis in antineutrophil cytoplasmic antibodyassociated vasculitis (AAV). He raises the interesting issue of susceptibility to both arterial and venous thrombotic events, which is also characteristic of antiphospholipid syndrome. The question arises as to the possible role of antiphospholipid antibodies (aPL) in the thrombotic events seen in AAV. We also thought that this possibility should be examined, but unfortunately our data on aPL are limited, because we studied a retrospective cohort in which these tests were not routinely performed. In fact, we tested for anticardiolipin IgG and IgM in only 49 of the 210 patients in the study. We found positive results in 3 patients, none of whom were in the group with thrombosis 2 . In the patients who had a thrombosis, we found negative results in 4 out of the 24 who had an arterial thrombosis, and 5 out of 14 who had a venous thrombosis. These findings were not reported in the original paper because of the low proportion of patients tested and because they were tested only at baseline.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.018 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".