The Motor Learning Strategy Instrument
Bibliographic record
Abstract
PURPOSE: To evaluate and compare the interrater reliability of the Motor Learning Strategy Rating Instrument (MLSRI) within usual and virtual reality (VR) interventions for children with acquired brain injury. METHODS: Two intervention sessions for each of 11 children (total, 22) were videotaped; sessions were provided by 4 physical therapists. Videotapes were divided into usual and VR components and rated by 2 observers using the MLSRI. A generalizability theory approach was used to determine interrater reliability for each intervention. RESULTS: Interrater reliability for usual interventions was high for the MLSRI total score (g-coefficient, 0.81), whereas it was low for the VR total score (g-coefficient, 0.28); MLSRI category g-coefficients varied from 0.35 to 0.65 for usual and from 0.17 to 0.72 for VR interventions. CONCLUSION: Adequate reliability was achieved within ratings of usual interventions; however, challenges related to MLSRI use to rate VR-based interventions require further evaluation.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".