The effects of single and dual obstacles on on-line processes during a manual obstacle avoidance task
Bibliographic record
Abstract
Perturbations to the upper limb in aiming tasks act to force individuals to modify their movements using on-line control processes. Studies show that individuals are able to successfully counteract these mechanical (e.g. Nashed et al., 2014) and perceptual perturbations (e.g. Elliott et al., 1995) to accurately acquire a specific target goal. A series of two studies were conducted to better understand the effects of a perceptual perturbation when performing two-dimensional sliding movements during a manual obstacle avoidance task when a second obstacle appeared unexpectedly within a preferred aiming path. On each trial, an obstacle appeared at 25%, 50% or 75% of the movement amplitude. On some trials, a second set of obstacles appeared early or later in the movement that forced participants to make on-line corrections or adapt their preferred trajectory to successfully reach the specified target. Results revealed that the possibility of the unexpected second obstacle influenced the overall trajectory and movement kinematics (i.e., whether that second obstacle appeared or not). Specifically, participants executed a more lateral avoidance trajectory and reached higher peak velocities and accelerations.. When the onset of the secondary set of obstacles occurred later into the movement, it resulted in individuals reaching peak velocities later in their movement which indicated that the possibility of a secondary perturbation resulted in more cautious movements. Results will be further discussed in the context of obstacle avoidance and movement planning behaviours as well as possible modifications to these behaviours in individuals with an Autism Spectrum Disorder.
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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 | 0.001 | 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".