Toward Appropriate Representations of Quantitative Data in Virtual Environments
Why this work is in the frame
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Bibliographic record
Abstract
Displays of quantitative data within three-dimensional (3D) virtual environments are quickly created with today's technological options, but we know little about the appropriateness of such representations. Based on two-dimensional (2D) cartographic knowledge and popular symbolization usage, six potentially appropriate proportional symbols for the display of quantitative data in virtual environments are experimentally tested: 2D bars, 3D bars, and 2D circles, with and without reference frames indicating the largest possible value. The results show that 2D bars are most efficient and effective, as evaluated through two elementary tasks (indicating the larger symbol and comparing symbol sizes); 3D bars are less and 2D circles least efficient and effective. The use of reference frames improves the effectiveness but not the efficiency of task completion.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 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