Feeling the future
Bibliographic record
Abstract
When a moving target is flashed briefly, the position of the flash is mislocalized in the direction of the motion (Cai & Schlag, 2001). A similar forward shift is also reported for the localization of a click added to a moving auditory target (Krüger et al, 2014). However, the reports for touch are mixed: the location of a tactile stimulus presented to a moving finger can be referenced forward in the direction of the finger’s motion (Dassonville, 1994; Watanabe et al, 2009) or backward (Maij et al, 2011). Our goal was to measure this tactile mislocalization and compare it to the auditory case under similar test conditions. We designed a simple tabletop procedure for both, one that could be easily duplicated for classroom use with no equipment. In the touch condition, blindfolded subjects moved their index finger 40 cm across a table leftward or rightward in about 500 ms, either voluntarily or passively. At mid-trajectory, there was a notch in the table that subjects could feel. After completing the hand movement, subjects pointed to the felt location of the notch. Surprisingly, subjects systematically mislocalized the notch backwards, closer to the beginning of their trajectory, when they moved their own hand but not when the experimenter moved it. In the auditory condition, blindfolded subjects passively listened to the sound of a key dragged across the table over the same trajectory, making a click as it passed over the notch. Here, they pointed to a location that placed the click ahead on its path. When subjects had both auditory and tactile information, dragging the key with their own hand, the mislocalizations cancelled. Our simple tabletop tests replicate forward mislocalizations in the auditory domain and suggest that under active control, the felt location of a moving hand lags its physical location. Meeting abstract presented at VSS 2015
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.063 | 0.011 |
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".