Bibliographic record
Abstract
This article describes changes in memory during the normal aging process from the standpoint of cognitive psychology. There is now a great deal of evidence to show that memory is not one single function but may be described in terms of different memory systems that show differential effects of aging. For example, memory for procedures, and some perceptual memory functions, show few age-related changes, whereas working memory, episodic memory, and prospective memory decline substantially in the course of normal aging. Memory for facts and knowledge (semantic memory) holds up well in older individuals provided that the information is used frequently, although the ability to retrieve highly specific information (such as names) typically declines. The article discusses current theoretical accounts of the effects of aging; different theorists have attributed the changes in memory and cognition to mental slowing, declining attentional resources, an inability to inhibit unwanted information, and a decline in cognitive control. Other suggestions include the notion that memory performance in older adults is particularly vulnerable when the need for self-initiated processing is greatest; conversely, performance is greatly helped by the provision of environmental support. The practical implications of these research findings and ideas include the point that clinical memory assessments should incorporate tests designed to measure the different aspects of memory functioning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.002 | 0.017 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".