Intelligent systems for interactive design and 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
Intelligent systems for interactive design and visualization require technologies that reliably generate surface and solid models from acquired spatial data, user hand gestures and verbal instructions; and seamlessly integrate this information into the overall product design process. The deformable spherical self-organizing feature map (SOFM) is a versatile modeling tool that is able to create 3D shapes from numerous arbitrarily ordered N-dimensional data vectors. The data may be surface points on existing objects or multi-dimensional feature vectors obtained through experimental observation. The SOFM develops a topologically ordered lattice that provides information about magnitude and connectivity between neighboring vectors in the original data space. The shapes generated by the deformable SOFM can be displayed, reoriented, analyzed, and modified in an immersive virtual reality environment (IVR). This paper describes how the spherical SOFM can be used to reconstruct the shape of an existing object from measured coordinate points and be modified using shape transformation techniques for virtual 3D free-form design.
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