A probabilistic approach to modeling two-dimensional pointing
Why this work is in the frame
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Bibliographic record
Abstract
We investigate and model two-dimensional pointing where the target distance and size vary as does the angle of movement. We first study the spread of hits in a rapid approximate pointing task at varied distances and movement angles. Consistent with the literature, our results show that the spread of hits along the movement direction deviate more than the spread of hits in the direction perpendicular to movement, and both spreads increase with distance. Based on the distribution of this spread of hits, we propose and validate a new probabilistic model that describes two-dimensional pointing. Unlike previous models, our model accounts for more variables of two-dimensional pointing and can be generalized to any target shape, size, orientation, location, and dimension. In contrast to previous work, which suggests that target height has minimal impact on performance when it is larger than the width, our results show that, even when height is greater than width, it can significantly impact movement time.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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