Bibliographic record
Abstract
Most of us do not often think about how we think, and that's probably just as well. Our language can circle around itself, often taking us up blind alleys, or into a complexity that is as irredeemable as it is irrelevant to daily practice. But sometimes we must give mind to our metaphors. For a long time we have thought of the brain in old age as an innocent bystander. It sometimes gets bruised and sometimes beaten up, but it's not as though it can do a lot about it. Other metaphors have competed, including the brain as repository, coming to old age with assets that inexorably dwindle, until they meet a threshold, after which disease occurs. In this issue, Wilson and colleagues1 report that people who habitually engage in high levels of cognitive activity showed less cognitive decline—and less often had Alzheimer disease (AD)—than did people with less cognitively activating routines. The Rush Memory and Aging Project is a prospective clinicopathologic study, whose 931 participants have agreed to annual examinations and brain autopsy. Its high retention rate (93.5% of people enrolled for more than 1 year average were followed 3.5 times on average) and detailed evaluations provide insights into the …
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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 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.015 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".