Vascular risk burden, brain health, and next steps
Bibliographic record
Abstract
In this issue of Neurology ®, Pase et al.1 on behalf of the Framingham Heart Study (FHS) investigators share the results of an epidemiologic analysis of both cross-sectional and longitudinal data of age-related influences of vascular risk factor burden on brain structure. The analysis included participants from the prospective, community-based FHS that comprised an Original cohort dating back to 1948, an Offspring cohort, and a Third Generation cohort (i.e., the grandchildren of the Original cohort). The cross-sectional portion of the study included 2,887 participants and an updated version of the Framingham Stroke Risk Profile (FSRP) calculated to assess their vascular risk factor burden. They examined the strength of association between the FSRP and brain volume across age decades from 45 to 54 years through 85–94 years. In the longitudinal portion of the study, they analyzed 40 years of data assessing the strength of association between vascular risk burden at earlier ages and brain volume changes among 7,968 participants.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.015 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 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".