Sleep and cognition in the elderly
Bibliographic record
Abstract
Understanding the role of sleep and the mechanisms at play in ageing are among the most exciting challenges in neuroscience. Although our understanding of the mechanisms governing sleep stages and their role in cognitive processes including memory functions is gradually increasing. most of the currently available data have been gathered in young adults. Still, substantial physiological changes in sleep are observed with increasing age, that may markedly impacts on daily functioning. This is why this Research Topic focuses on our current understanding of the impact of age-related changes in sleep architecture on various domains of cognition. The three editors Julie Carrier (Montréal, Canada), Philippe Peigneux (Brussels, Belgium) and Géraldine Rauchs (Caen, France) are specialized in various fields of sleep research. Here, they bring together an outstanding group of neuroscientist and clinical investigators engaged in the study of sleep, encompassing state-of-the-art studies of sleep disorders such as sleep apnoea or REM sleep behaviour disorder, studies assessing new treatments to improve sleep quality, together with experts in various domains of cognition such as vigilance, memory and dreams, in a perspective aimed at offering the interested reader a comprehensive view of the impact of age-related changes in sleep architecture on cognition.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".