A postural adaptation test for stroke patients
Bibliographic record
Abstract
PURPOSE: To explore the interrater reliability of the Advanced Mobility and Balance Scale (AMBS) and to determine its discriminative capacity in stroke patients. METHODS: Twelve hemiparetic patients and six healthy elderly volunteers were videotaped while: (1) executing rapid head motions during standing and walking; and (2) standing and walking on a slope. Five physical therapists viewed the videotapes to establish interrater reliability. RESULTS: Interrater reliability: Intraclass correlation ratios ranged from 0.93-0.97 for the AMBS global as well as slope and head turn subscores. Construct validity: One-way ANOVAs and post-hoc pairwise comparisons were performed to determine whether there was a difference in scores between high (HFL) and low functional-level (LFL) stroke patients (based on gait speed) and healthy subjects. Mean (+/-SD) global scores were 45 +/- 3 for healthy subjects, 40 +/- 9 for HFL stroke patients and 25 +/- 1 for LFL stroke patients (p < 0.05 for HFL versus LFL patients and LFL patients versus healthy subjects). The AMBS slope subscores were 22 +/- 2, 19 +/- 5, 9 +/- 7 for healthy, HFL and LFL subjects respectively (p < 0.05 for HFL versus LFL patients and LFL patients versus healthy subjects). CONCLUSION: The AMBS has excellent interrater reliability and good discriminative capacities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.004 | 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".