An Evaluation of Interaction Methods for Controlling RSVP Displays in Visual Search Tasks
Bibliographic record
Abstract
Accurately identifying images with subtly varying features from a large set of similar images can be a challenging task. To succeed, viewers must perceive subtle differences between multiple nearly identical images and react appropriately. The Rapid Serial Visual Presentation (RSVP) display technique has the potential to improve performance as it exploits our ability to preattentively recognize differences between images when they are flashed on a screen in a rapid and serial manner. We compared the speed and accuracy of three RSVP interface methods ("Hover", "Slide Show" and "Velocity") against a traditional "Point & Click" non-RSVP interface to test whether an RSVP display improves performance in visual search tasks. In a follow-up study we compared "Hover" and "Velocity" RSVP interface methods against a "Small Multiples" non-RSVP interface to explore the interaction of interface type and target size on visual search tasks. We found the "Hover" RSVP interface to significantly reduce the time it takes to perform visual search tasks with no reduction in accuracy, regardless of the size of the search targets. Beyond the gene identification task tested here, these experiments inform the design of user interfaces for many other visual search tasks.
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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 | 0.003 | 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 | 0.001 |
| 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".