Bibliographic record
Abstract
OBJECTIVES: The objectives of this Introduction to the Journal of Gerontology: Psychological Sciences special issue on "50 Years of Cognitive Aging Theory" are to provide a brief overview of cognitive aging research prior to 1965 and to highlight significant developments in cognitive aging theory over the last 50 years. METHOD: Historical and recent theories of cognitive aging were reviewed, with a particular focus on those not directly covered by the articles included in this special issue. RESULTS: Prior to 1965, cognitive aging research was predominantly descriptive, identifying what aspects of intellectual functioning are affected in older compared with younger adults. Since the mid-1960s, there has been an increasing interest in how and why specific components of cognitive domains are differentially affected in aging and a growing focus on cognitive aging neuroscience. DISCUSSION: Significant advances have taken place in our theoretical understanding of how and why certain components of cognitive functioning are or are not affected by aging. We also know much more now than we did 50 years ago about the underlying neural mechanisms of these changes. The next 50 years undoubtedly will bring new theories, as well as new tools (e.g., neuroimaging advances, neuromodulation, and technology), that will further our understanding of cognitive aging.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".