Documentation of daily sit-to-stands performed by community-dwelling adults
Bibliographic record
Abstract
No information exists about how many sit-to-stands (STSs) are performed daily by community-dwelling adults. We, therefore, examined the feasibility of using a tally counter to document daily STSs, documented the number of daily STSs performed, and determined if the number of STSs was influenced by demographic or health variables. Ninety-eight community-dwelling adults (19-84 years) agreed to participate. After providing demographic and health information, subjects used a tally counter to document the number of STSs performed daily for 7 consecutive days. All but two subjects judged their counter-documented STS number to be accurate. Excluding data from these and two other subjects, the mean number of STSs for subjects was 42.8 to 49.3, depending on the day. The number was significantly higher on weekdays than weekends. No demographic or health variable was significantly related to the number of STSs in univariate or multivariate analysis. In conclusion, this study suggests that a tally counter may be a practical aid to documenting STS activity. The STS repetitions recorded by the counter in this study provide an estimate of the number of STSs that community-dwelling adults perform daily.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".