Identification of predictors of bone mineral density trajectories in pediatric Systemic Lupus Erythematosus patients
Bibliographic record
Abstract
Results Females constituted 84% of the cohort with a median age at diagnosis of 13.1 years. The mean LS BMD zscores decreased with time. Initially, 9% of patients had a low BMD, this proportion increased to 19% by 3 years after diagnosis. Overall, the BMD category decreased in 35% of patients from 1 to 3rd DEXA study. LS BMD followed a general deteriorating trajectory of -0.25 z-score/year from diagnosis. Body mass index (BMI) z-score and cumulative steroid dose were the best predictors of BMD trajectories over time. Conclusions The LS BMD of pSLE patients decreased at a rate of 0.25 z-score/year. BMI z-score and cumulative doses of steroids modified the trajectories of LS BMD. These factors are potentially modifiable targets that can improve individual patient’s BMD trajectory.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".