Studying direct-touch interaction for 2D flow visualization
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
Abstract—Traditionally, scientific visualization research concentrates on the development and improvement of interactive techniques to support expert data analysis. While many scientific visualization tools have been developed for desktop environments and individual use, scenarios that go beyond mouse and keyboard interaction have received considerably less attention. We present a study that investigates how large-display direct-touch interaction affects data exploration and insight generation among groups of nonexperts exploring 2D vector data. In this study, pairs of participants used interaction techniques to customize and explore 2D vector visualizations and collaboratively discussed the process to develop their own understanding of the data sets. Index Terms—Interactive scientific visualization, direct-touch interaction, wall displays, qualitative evaluations, 2D vector visualization. 1
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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 | 0.001 |
| 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 it