Efficient use of the BlobTree for rendering purposes
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
One of the major applications of implicit surface modeling systems has been the generation of cartoon-like characters. Recently, additional modeling methods have been combined with implicit surfaces to create much more complex models. These methods include constructive solid geometry (CSG), warping, and two-dimensional texture mapping (among others). The BlobTree has been introduced to organize all of these elements into a single structure which allows both local and global applications of each of these techniques in a general and intuitive fashion. The BlobTree lends itself well to rapid and direct specification of complex models, however current implementations of the BlobTree have not been engineered for efficiency, and perform poorly when attempting to render large models. In this work we apply established techniques, such as spatial subdivision and tree optimization, to the BlobTree. The objective is to increase efficiency during rendering without restricting the functionality of the BlobTree as a modeling tool.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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