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Record W2153707367 · doi:10.1080/10255840601022734

Computational model of the movement of the human muscles of mastication during opening and closing of the jaw

2006· article· en· W2153707367 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputer Methods in Biomechanics & Biomedical Engineering · 2006
Typearticle
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMasticationTemporomandibular jointMuscles of masticationAnatomyMandible (arthropod mouthpart)CadaverMovement (music)Closing (real estate)BundleSkullAnimationComputer scienceOrthodonticsMedicineBiologyMaterials scienceComputer graphics (images)Physics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.369
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it