The role of internal forward models and proprioception in hand position estimation
Why this work is in the frame
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Bibliographic record
Abstract
Our ability to properly move and react in different situations is largely dependent on our perception of our limbs' position. At least three sources - vision, proprioception, and internal forward models (FMs) - seem to contribute to this perception. To the best of our knowledge, the effect of each source has not been studied individually. Specifically, role of FM has been ignored in some previous studies. We hypothesized that FM has a critical role in subjects' perception which needs to be considered in the relevant studies to obtain more reliable results. Therefore, we designed an experiment with the goal of investigating FM and proprioception role in subjects' perception of their hand's position. Three groups of subjects were recruited in the study. Based on the experiment design, it was supposed that subjects in different groups relied on proprioception, FM, and both of them for estimating their unseen hand's position. Comparing the results of three groups revealed significant difference between their estimation' errors. FM provided minimum estimation error, while proprioception had a bias error in the tested region. Integrating proprioception with FM decreased this error. Integration of two Gaussian functions, fitted to the error distribution of FM and proprioception groups, was simulated and created a mean error value almost similar to the experimental observation. These results suggest that FM role needs to be considered when studying the perceived position of the limbs. This can lead to gain better insights into the mechanisms underlying the perception of our limbs' position which might have potential clinical and rehabilitation applications, e.g., in the postural control of elderly which are at high risk of falls and injury because of deterioration of their perception with age.
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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 | 0.001 | 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 | 0.001 |
| 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 it