Haptic object recognition is influenced by the orientation of the body relative to gravity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The orientation at which objects are most easily recognized — the perceptual upright (PU) — is influenced by body orientation with respect to gravity. To date, the influence of these cues on object recognition has only been measured within the visual system. Here we investigate whether objects explored through touch alone are similarly influenced by body and gravitational information. Using the Oriented CHAracter Recognition Test (OCHART) adapted for haptics, blindfolded right-handed observers indicated whether the symbol ‘p’ presented in various orientations was the letter ‘p’ or ‘d’ following active touch. The average of ‘p-to-d’ and ‘d-to-p’ transitions was taken as the haptic PU. Sensory information was manipulated by positioning observers in different orientations relative to gravity with the head, body, and hand aligned. Results show that haptic object recognition is equally influenced by body and gravitational references frames, but with a constant leftward bias. This leftward bias in the haptic PU resembles leftward biases reported for visual object recognition. The influence of body orientation and gravity on the haptic PU was well predicted by an equally weighted vectorial sum of the directions indicated by these cues. Our results demonstrate that information from different reference frames influence the perceptual upright in haptic object recognition. Taken together with similar investigations in vision, our findings suggest that reliance on body and gravitational frames of reference helps maintain optimal object recognition. Equally relying on body and gravitational information may facilitate haptic exploration with an upright posture, while compensating for poor vestibular sensitivity when tilted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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