Static pose reconstruction with an instrumented bouldering wall
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
This paper describes the design and construction of an instrumented bouldering wall, and a technique for estimating poses by optimizing an objective function involving contact forces. We describe the design and calibration of the wall, which can capture the contact forces and torques during climbing while motion capture (MoCap) records the climber pose, and present a solution for identifying static poses for a given set of holds and forces. We show results of our calibration process and static poses estimated for different measured forces. To estimate poses from forces, we use optimization and start with an inexpensive objective to guide the solver toward the optimal solution. When good candidates are encountered, the full objective function is evaluated with a physics-based simulation to determine physical plausibility while meeting additional constraints. Comparison between our reconstructed poses and MoCap show that our objective function is a good model for human posture.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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