Effect of History Trail Display on Human Spatial Performance under Normal and Rotated Spatial Mappings
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
In a rotated visual-motor mapping environment, human spatial performance is seriously affected by misaligned visual and motor reference axes, resulting in elevated spatial errors. In this paper, we propose a history trail display in an augmented reality setting. We investigate the effectiveness of the display in consecutive aiming tasks, under normal visual-motor mapping, as well as mappings with 90°, 135°, and 180° rotations. Spatial movement error and the smoothness of the trajectories were measured and compared between the history trail display and the regular video display. Our results show that, under normal mapping condition, the history trail appears to help reduce the spatial movement error and improve the smoothness of the movement trajectories. With rotated mappings, the benefit of the history trail becomes significant only after a certain degree of adaptation to the rotated mappings has been attained. The history trail appears to enhance the perception of errors, movement direction, and speed information for error-correcting processes during the aiming movements.
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 | 0.000 |
| 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