Reaching-to-eat in humans post-stroke: Fluctuating components within a constant pattern.
Bibliographic record
Abstract
Reaching movements of the arm and hand become automatic early in development and are used throughout one's life span. Studies on skilled reaching have focused on the kinematic aspects and have advanced our knowledge of the individual motor components of reaching. It has also been shown that motor behaviors are organized in terms of ethologically relevant actions, rather than by motor components. Thus, it is important to analyze how the motor components of reaching are performed within the overall action as a whole. The objective of the present study was to examine the motor components of reaching-to-eat within the context of the overall behavior in stroke participants. Results show that reaching-to-eat involves the whole body to produce isolated actions of the limb and changes after stroke in three fundamental ways: abnormal use of nonkinematic aspects of movement, body-limb disintegration, and a disruption in the temporal aspect of the phases of reaching-to-eat. The movements within the behavior can reorganize, possibly a reflection of dynamic interactions between behavioral compensation and neuroplasticity, while the overall performance of the behavior remains the same. Such subtle flexibility may be part of the process of recovery.
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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 | 0.001 |
| 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".