Effects of 2D geometric transformations on visual memory
Bibliographic record
Abstract
In order to provide well-grounded guidelines for interface design, we systematically examined the effects of 2D geometric transformations and background grids on visual memory. We studied scaling, rotation, rectangular fisheye, and polar fisheye transformations. Based on response time and accuracy results, we found a no-cost zone for each transformation type within which performance is unaffected. Results indicated that scaling had no effect down to at least 20% reduction. Rotation had a no-cost zone of up to 45 degrees, after which the response time increased to 5.4 s from the 3.4 s baseline without significant drop in accuracy. Interestingly, polar fisheye transformations had less effect on accuracy than their rectangular counterparts. The presence of grids extended these zones and significantly improved accuracy in all but the fisheye polar transformations. Our results therefore provided guidance on the types and levels of nonlinear transformations that could be used without affecting performance, and provided insights into the roles of transformations and grids on visual memory.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".