The role of feedback on cognitive motor learning in children with cerebral palsy: A protocol
Bibliographic record
Abstract
Evidence of provision of extrinsic feedback for improvement and retention of upper limb kinematics in children with cerebral palsy (CP) is scarce, especially following training interventions using virtual environments. Benefits of using a virtual environment can range from increasing the participant's motivation to the ease of adapting extrinsic feedback for optimizing motor learning. In the proposed research, children with CP will be randomly allocated to one of three groups: no additional feedback, continuous feedback and faded feedback. For all groups, upper-limb motor training will be done in a virtual environment using the Jintronix virtual reality system. Motor improvements will be evaluated after an 8 hour training intervention and motor learning will be evaluated after one month. Transfer of motor gains to performance of a similar upper-limb task will also be used to assess learning. Findings from this research will provide crucial information on which frequency of feedback should be used to optimize motor learning and upper-limb rehabilitation in children with CP.
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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 | 0.018 | 0.018 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.044 | 0.008 |
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".