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
We present an intuitive animation interface that uses a foot pressure sensor pad to interactively control avatars for video games, virtual reality, and low-cost performance-driven animation. During an offline training phase, we capture full body motions with a motion capture system, as well as the corresponding foot-ground pressure distributions with a pressure sensor pad, into a database. At run time, the user acts out the animation desired on the pressure sensor pad. The system then tries to see the motion only through the foot-ground interactions measured, and the most appropriate motions from the database are selected, and edited online to drive the avatar. We describe our motion recognition, motion blending, and inverse kinematics algorithms in detail. They are easy to implement, and cheap to compute. FootSee can control a virtual avatar in a fixed latency of 1 second with reasonable accuracy. Our system thus makes it possible to create interactive animations without the cost or inconveniences of a full body motion capture system.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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