Size-weight illusion dissociates from grip forces when objects lifted from other hand
Bibliographic record
Abstract
When lifting two visible objects of the same weight but different volumes, the smaller object is judged to be the heavier. It has been suggested that the illusion arises from a mismatch between expectation and sensory feedback. To clarify the role of sensory feedback, we measured estimates of heaviness and precision-grip forces when participants lifted objects (1331 cm3 and 147 cm3; 0.33 kg each) that were resting either on a table or on the palm of their other hand. Testing order was counterbalanced across participants and object size was alternated randomly between trials. A robust size-weight illusion, as evidenced by the ratio of small-to-large heaviness estimates (average: 1.42), was observed in both the table and palm conditions, with the table condition showing a slightly stronger illusion (1.55 vs. 1.29). Participants who first lifted the objects from the table (without first lifting the object from the palm of their other hand) generated peak grip forces that were significantly greater for the larger of the two objects. After that initial lift, however, the grip forces applied to the two objects rapidly converged and remained so for the rest of the experiment. In contrast, participants who first lifted objects from the palm applied equivalent grip forces to both objects on the very first trial and continued to do so for the remainder of the experiment. These results suggest that even though the lifting hand can use information from the supporting hand to scale grip forces accurately, the size-weight illusion is only slightly diminished.
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.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".