Aging, the Central Nervous System, and Mobility
Bibliographic record
Abstract
BACKGROUND: Mobility limitations are common and hazardous in community-dwelling older adults but are largely understudied, particularly regarding the role of the central nervous system (CNS). This has limited development of clearly defined pathophysiology, clinical terminology, and effective treatments. Understanding how changes in the CNS contribute to mobility limitations has the potential to inform future intervention studies. METHODS: A conference series was launched at the 2012 conference of the Gerontological Society of America in collaboration with the National Institute on Aging and the University of Pittsburgh. The overarching goal of the conference series is to facilitate the translation of research results into interventions that improve mobility for older adults. RESULTS: Evidence from basic, clinical, and epidemiological studies supports the CNS as an important contributor to mobility limitations in older adults without overt neurologic disease. Three main goals for future work that emerged were as follows: (a) develop models of mobility limitations in older adults that differentiate aging from disease-related processes and that fully integrate CNS with musculoskeletal contributors; (b) quantify the contribution of the CNS to mobility loss in older adults in the absence of overt neurologic diseases; (c) promote cross-disciplinary collaboration to generate new ideas and address current methodological issues and barriers, including real-world mobility measures and life-course approaches. CONCLUSIONS: In addition to greater cross-disciplinary research, there is a need for new approaches to training clinicians and investigators, which integrate concepts and methodologies from individual disciplines, focus on emerging methodologies, and prepare investigators to assess complex, multisystem associations.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".