Do pointing responses account for proprioceptive drift
Bibliographic record
Abstract
While performing multiple back and forth pointing movements when vision of the hand is unavailable, movements can gradually drift away from their intended target (Brown et al., 2003). Although imperceptible to the participant, these movements can drift substantially soon after the initiation of the trial (e.g., within 5-10 reaches). The purpose of this study was to determine the level of "awareness" that people have of this drift in limb position. For example, if presented with a new target after a movement has drifted, do we rely on our actual limb position ("drifted off target") or our believed position ("on target") to reach the new target? To explore this question, participants performed back and forth pointing movements with vision of the targets and fingertip for the first 10 seconds of every trial, followed by a period (~45 s) of continuous pointing with or without vision of the hand (cursor). During this latter period, the original targets disappeared and a new target appeared at -5 cm, 0 cm, or +5 cm relative to the original target locations. We expected that if participants were able to base their pointing on their actual unseen (and off target) limb position, they would point accurately to the new location. However, if participants remained unaware that their limb position had drifted, their pointing would be reflective of locations defined relative to the original targets. Our results suggest that participants pointed to the new targets based on the perception that there was no drift in limb position.Acknowledgments: Supported by the Natural Sciences and Engineering Research Council of Canada
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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 | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".