The Visual Regulation of Goal-Directed Reaching Movements in Adults with Williams Syndrome, Down Syndrome, and Other Developmental Delays
Bibliographic record
Abstract
Williams syndrome (WS) is a genetic disorder that causes general cognitive and developmental delays. Compared to persons with Down syndrome (DS) at the same developmental level, individuals with WS generally exhibit superior expressive language abilities, but have difficulty with tasks that require the visual control of movement. Recently it has been suggested that this latter problem reflects a deficit in dorsal stream function. In the present study, this hypothesis was investigated by examining the kinematics of rapid aiming movements. The performance of the participants with WS (n=4) was compared to the performance of participants with DS (n=8), with undifferentiated developmental delays (n=8), and from the general population (n=8). In partial support of the dorsal deficit hypothesis, the results suggest that, compared to people from the other groups, the participants with WS had difficulty in preparing their movements on the basis of the visual and other information available to them. This was particularly evident in their inability to properly scale movement velocities to the amplitude of the movements and in the number of discrete corrections made during movement execution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".