Calibration of Multi-Axis MEMS Force Sensors Using the Shape-From-Motion Method
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Bibliographic record
Abstract
Precise calibration of multi-axis microelectromechanical systems (MEMS) force sensors is difficult for several reasons, including the need to apply many known force vectors at precise orientations at the micro- and nanoNewton (nN) force scales, and the risk of damaging the small, fragile microdevices. To tackle these challenges, this paper introduces the shape-from-motion calibration method. A new design of a two-axis MEMS capacitive force sensor with high linearity and nN resolutions is presented. Structural-electrostatic coupled-field simulations are conducted in order to optimize the sensor design. The designed sensor is calibrated with the shape-from-motion method, the least-squares method as well as the gravity-based method for comparison purposes. Calibration results demonstrate that the shape-from-motion method provides a rapid, practical, and accurate technique for calibrating multi-axis MEMS sensors
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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 | 0.001 | 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