ACM: atlas of connectivity maps for semiregular models
Why this work is in the frame
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Bibliographic record
Abstract
Semiregular models are an important subset of models in computer graphics. They are typically obtained by applying repetitive regular refinements on an initial arbitrary model. As a result, their connectivity strongly resembles regularity due to these refinement operations. Although data structures exist for regular or irregular models, a data structure designed to take advantage of this semiregularity is desirable. In this paper, we introduce such a data structure called atlas of connectivity maps for semiregular models resulting from arbitrary refinements. This atlas maps the connectivity information of vertices and faces on separate 2D domains called connectivity maps. The connectivity information between adjacent connectivity maps is determined by a linear transformation between their 2D domains. We also demonstrate the effectiveness of our data structure on subdivision and multiresolution applications.
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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 | 0.000 |
| 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 it