A step and a shift: Examining sensory-motor control of goal-directed aiming
Bibliographic record
Abstract
Sex differences in the control of manual aiming have been demonstrated following target perturbations and under prismatic displacement. However, the locus of these differences has yet to be explained beyond evolutionary or socio-cultural theories. This study examined potential sensory-motor control differences between males and females using a double-step perturbation paradigm. Eighteen participants were recruited (9 Females). Participants aimed at a square (0.5cm2 at 40cm within the midline) as quickly and as accurately as possible. Perturbations occurred at movement initiation (MI) and then at 100ms after MI. Target perturbations included a 12cm displacement to the left or right or none. Prismatic displacement was achieved with liquid crystal goggles switching from the right lens with normal vision to the left lens that had either a 30-diopter Fresnel prism (17degrees) or a placebo lens. In total, there were 12 conditions: 2-Order (Target 1st, Target 2nd) by 3-Target (Left, Centre, Right) by 2-Prism (None, Right). 3D Position was recorded by a Certus at 500Hz for 2s. Participants landed farther from the target when the prism was presented compared to the placebo lens regardless of whether the prism was presented first or second. When the prism was presented at MI, participants displayed more error than when it was presented at 100ms. Males had shorter movement time, especially when the placebo lens was presented at MI and then the target remained at the centre. Results indicate the necessity to revisit modern models of goal-directed aiming with the intention of incorporating individual differences in sensory-motor control.
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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 | 0.000 | 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) | 0.003 | 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".