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Record W4253888129 · doi:10.1155/2012/324034

A Mastication Mechanism Designed for Testing Temporomandibular Joint Implants

2012· article· en· W4253888129 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

VenueApplied Bionics and Biomechanics · 2012
Typearticle
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsWestern University
Fundersnot available
KeywordsTemporomandibular jointMasticationImplantJoint (building)Mechanism (biology)OrthodonticsMaterials scienceBridge (graph theory)Biomedical engineeringCompression (physics)Computer scienceDentistryStructural engineeringEngineeringMedicineAnatomySurgeryComposite materialPhysics

Abstract

fetched live from OpenAlex

The development of temporomandibular joint implants has involved simplified mechanical tests that apply pure vertical forces or pure rotational movements to the implant. The aim of this study was to develop a biological based mastication mechanism and conduct preliminary testing of a novel temporomandibular joint implant. The mechanism was designed to mimic temporomandibular joint loads by performing compression and anterior/posterior translation. Pilot testing was performed on six implant/joint specimens for seven consecutive hours, completing approximately 22,000 cycles at a frequency of approximately 1 Hz. Each cycle had a joint compression phase (67.3 N over 0.15 s) followed by a translation phase (8.67 N over 0.43 s) that was similar to joint loads/motions that have been reported in vivo. This new mastication mechanism incorporates both anatomical and mechanical variability. The use of biological specimens is an important approach that can help bridge the gap between traditional synthetic implant materials/mechanical testing and in vivo testing.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.535
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.097
GPT teacher head0.350
Teacher spread0.253 · 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