Introducing the Head-Mounted Rotating Drum
Bibliographic record
Abstract
The rotating drum is a classic apparatus used to study circular vection – the visually induced illusion of self-rotation in a stationary observer. The observer sits in a large cylinder that has an illuminated interior, consisting of black and white vertical stripes that occupy the entire visual field. The drum and hence the stripes can rotate and make the seated observer feel that s/he is rotating in the direction opposite to the motion of the stripes. Advances in head-mounted display (HMD) technology have allowed researchers to induce vection using HMDs. For the first time, our group has replicated the rotating drum in a virtual reality HMD environment. We manipulated the simulated speed of the rotating drum, and recorded participant vection perception. Vection was measured and recorded by having participants rotate a circular knob capable of spinning infinitely in clockwise and counter-clockwise directions, while viewing the moving stripe pattern within the HMD. Participants were instructed to monitor their sensation of rotary vection and turn the knob in the direction opposite to their perceived self-rotation. Knob rotation speeds and rotation times are recorded and used to indicate vection strength. Knob rotation methods have been used in previous research to measure vection, however ours is a unique alteration in that 1)the rotation of the knob does not control the visual display 2)participants turn the knob in the direction opposite to their perceived self-rotation. Our method is proving to be direct and informative for measuring circular vection. Data suggest that 1)the HMD is capable of inducing vection, similarly to the classic rotating drum apparatus 2)vection strength varies as a function of the simulated rotation speed of the visual display. This study further validates the use of HMDs for studying self-motion as it has allowed us to integrate a classically used apparatus within an HMD. Meeting abstract presented at VSS 2016
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".