Computational model of the movement of the human muscles of mastication during opening and closing of the jaw
Bibliographic record
Abstract
Muscle fibre bundles comprising the four major muscles of mastication in the human being were studied in cadavers. Markers were placed along each muscle fibre bundle by means of serial dissections. The 3D coordinates of each marker were tabulated and imported to Cinema 4D, a software animation program. Origins and insertions of each fibre bundle were also digitized and imported, as were the coordinates of the surface of the skull, the mandible and temporomandibular joint. It was then possible to visualize the movement of all relevant fibre bundles during the passive motions of the mandible. An animated film depicts the positions of all relevant muscle fibres during passive movement of the mandible. The properties of the masseter muscle were documented as a prototype for the eventual study of all the muscles of mastication. One can now proceed to study the inverse problem, namely the forces within each fibre bundle that actively generate mandibular motion. It is hoped that these studies will aid in the management of conditions affecting the temporomandibular joint.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".