Which trunk inclination directions best predict multidirectional-seated limits of stability among individuals with spinal cord injury?
Bibliographic record
Abstract
OBJECTIVE: To determine which trunk inclination directions most accurately predict multidirectional-seated limits of stability among individuals with spinal cord injury (SCI). DESIGN: Predictive study using cross-sectional data. SETTING: Pathokinesiology Laboratory. PARTICIPANTS: Twenty-one individuals with complete or incomplete sensorimotor SCI affecting various vertebral levels participated in this study. INTERVENTIONS: Participants were instructed to lean their trunk as far as possible in eight directions, separated by 45° intervals, while seated on an instrumented chair with their feet positioned on force plates. OUTCOMES MEASURES: Eight direction-specific stability indices (DSIs) were used to define an overall stability index (OSI) (limits of stability). RESULTS: All DSIs significantly correlated with the OSI (r = 0.816-0.925). A protocol that only tests the anterior, left postero-lateral, and right lateral trunk inclinations accurately predicts multidirectional-seated postural stability (r(2) = 0.98; P < 0.001). CONCLUSION: Multidirectional-seated postural stability can be predicted almost perfectly by evaluating trunk inclinations performed toward the anterior, left postero-lateral, and right lateral directions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".