Validity of the Comprehensive High-Level Activity Mobility Predictor in a heterogeneous population with lower extremity amputations
Bibliographic record
Abstract
Background and objective: Lower extremity amputee outcome measures assess basic mobility. The Comprehensive High-Level Activity Mobility Predictor was developed to assess high-level mobility. Validity evidence was collected in military men with traumatic lower extremity amputations. This study examines its validity in a broader population. Study design: Cross-sectional. Methods: Forty-five lower extremity amputees (Medicare Functional Classification Level K3 or K4) completed the 2-min walk test, Amputee Mobility Predictor with Prosthesis, and Comprehensive High-Level Activity Mobility Predictor. Results: The Comprehensive High-Level Activity Mobility Predictor correlated with the Amputee Mobility Predictor with Prosthesis (r = 0.77, p < 0.01) and the 2-min walk test (r = 0.65, p < 0.01). The Comprehensive High-Level Activity Mobility Predictor differentiated between K-levels, age groups, etiology of amputation, and amputation level (p < 0.005). No ceiling effect was observed (range: 2.5–29/40). Conclusion: This study provides convergent and discriminative validity evidence for Comprehensive High-Level Activity Mobility Predictor use in a more heterogeneous population than previously published, suggesting that clinicians should feel confident to use it as an outcome measure for individuals with amputations who are capable of more than level-ground walking. Clinical relevance Clinically, the Comprehensive High-Level Activity Mobility Predictor has validity evidence for use in a more heterogeneous population than originally demonstrated, including civilians, women, people over age 40 years, and non-traumatic etiologies. The Comprehensive High-Level Activity Mobility Predictor may be more useful than standard outcome measures for high-level mobility.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".