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
An adaptive modeling approach that uses a self-organizing feature map (SOFM) to create deformable hexahedral meshes for interactive geometric modeling is presented in this paper. The technique uses the nodes of a three-dimensional SOFM to represent discrete point masses that comprise a solid object. Although the geometry of the resultant mass-spring mesh will change under the influence of inputs applied through a haptic tool and interface, the relative connectivity of neighboring nodes in the time-varying mesh are maintained under the external and internal forces. The initial mesh can either be retrieved from a library of primitive shapes, or created by automatically fitting the topology preserving SOFM to selected surface points. The designer reshapes the virtual object by applying external forces and pressure to the initial mesh. The accuracy of the system depends on the mathematical equations used in formulating the model behavior. The model behavior can be altered by changing the material properties in the underlying mathematical equation. Examples of shape deformation are provided to illustrate the concepts introduced.
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 | 0.001 |
| 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