Time Course Analysis of Closed- and Open-Loop Grasping of the Müller-Lyer Illusion
Bibliographic record
Abstract
The authors investigated whether the early or later stages of closed-loop (CL) and open-loop (OL) grasping movements were differentially influenced by the Müller-Lyer (ML) illusion. Participants (N = 21) reached out and grasped small (5 cm) and large (7 cm) objects embedded within fins-in and fins-out ML configurations. Grasping time (GT) was normalized, and absolute grip aperture (GA) as well as scaled illusion effects were computed at 20%, 40%, 60%, and 80% of GT. The results indicated that CL trials were refractory to the illusory array (i.e., from 20% to 80% of GT), whereas OL trials were influenced by the ML figure during that same time. Those findings suggest that CL trials were supported by unitary and metrical visual information, whereas OL trials were entirely supported by perception-based visual information.
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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 | 0.002 |
| 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) | 0.001 | 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".