Can Failure on Adaptive Locomotor Tasks Independently Predict Incident Mobility Disability?
Bibliographic record
Abstract
This study examined whether inability to perform adaptive locomotor tests predicts self-reported incident mobility disability. InCHIANTI study participants (N = 611; age, 50-85 yrs) who could walk 7 m at self-selected speed and who had no self-reported mobility disability at baseline were included. The ability to complete four adaptive locomotor tests was assessed: fast walking, walking on a narrow path, crossing obstacles while walking, and talking while walking. Mobility disability was recorded again at 3-yr follow-up. Failure in the fast-walking and narrow-path walking tests predicted approximately 2.5 times likelihood of reporting incident mobility disability (P = 0.009 and P = 0.011, respectively). Failure in the obstacle-crossing test predicted approximately two times likelihood of reporting incident mobility disability; however, this result did not reach statistical significance (P = 0.077). Failure in talking while walking did not predict incident mobility disability. Those who failed both the fast-walking and narrow-path walking tests were almost nine times as likely to report incident mobility disability.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".