A Recommended Method for Obtaining the Age at Onset of Dementia From the CSHA Database
Bibliographic record
Abstract
In studies of dementia, the age at onset (AAO) of the disease is often described without indicating how it was obtained. We used the "CAMDEX algorithm," an ad hoc procedure, to compute the AAO of dementia from the CSHA database. An AAO could be calculated for 983 of 1,132 subjects with dementia. A similar procedure (the "clinical algorithm") was used to calculate a second AAO, which was compared to that obtained by the first algorithm. The CAMDEX and clinical algorithms produced mean AAOs of dementia of 80.5 years (SD = 9.2 years, n = 983) and 79.6 years (SD = 9.7 years, n = 829), respectively. The sample correlation coefficient between the CAMDEX and clinical algorithms was .899 while the intraclass correlation coefficient, ICC(2,1), was .898. This method could prove useful for researchers using the CSHA data who need an AAO for those subjects with dementia.
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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 | 0.029 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.016 |
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".