Tongue kinematics in palate relative coordinate spaces for electro-magnetic articulography
Bibliographic record
Abstract
This paper describes a method for constructing a three-dimensional model of the hard palate using electro-magnetic articulography, and defines two algorithms to derive constriction degree and constriction location values from the trajectories of tongue coils using this model. The kinematics of tongue motion that have been transformed into constriction degree and constriction location values are investigated in detail to determine whether this type of representation obeys the constraints theorized to operate over higher level motor control. Results show that palate-relative coordinate spaces decouple mechanical dependencies present in the tongue, while maintaining low-level kinematic properties. They additionally preserve the 1/3 power law for speed and curvature observed across many motor systems. Finally, it is shown that tongue movements in a palate relative coordinate space more closely correspond to their optimal, jerk-minimized trajectories. These results suggest that this type of coordinate space provides a closer match to higher level motor-planning, in line with production models that specify control units in terms of vocal tract constriction parameters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".