Observation Period Effects on Estimation of Systemic Lupus Erythematosus Incidence and Prevalence in Quebec
Bibliographic record
Abstract
OBJECTIVE: To determine how duration of observation affects estimation of incidence and prevalence of systemic lupus erythematosus (SLE). METHODS: SLE incidence and prevalence estimates from data periods as brief as 3 years (2001-2003) were compared to estimates from a 15-year period (1989-2003). RESULTS: The 15-year period incidence was 5.6/100,000 (95% CI 5.0-6.1) and the prevalence was 59.1/100,000 (95% CI 57.4-60.8). When a 3-year period was used, incidence was overestimated by 238.1% and prevalence underestimated by 66.0%. CONCLUSION: SLE incidence and prevalence estimates vary considerably according to the observation period; more than 5 years of data is likely required.
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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 | 0.012 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".