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Record W1987078357 · doi:10.5430/jbgc.v5n1p28

The influence of bite force strength on brain activity: A functional magnetic resonance imaging study

2015· article· en· W1987078357 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Biomedical Graphics and Computing · 2015
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFunctional magnetic resonance imagingMagnetic resonance imagingNuclear magnetic resonanceMedicineMaterials sciencePsychologyNeurosciencePhysicsRadiology

Abstract

fetched live from OpenAlex

In recent years, functional magnetic resonance imaging has been used to determine the interaction between chewing and brainactivity. However, the factors influencing the activity of the motor cortex have not been fully elucidated. Therefore, the presentstudy investigated the influence of the magnitude of bite force on brain activity. Fifteen right-handed healthy subjects (24-32 years; mean age, 27.8 years) were included. Sustained, constant clenching with small and large forces comprised the motortask. The spatial extent of the functional magnetic resonance imaging signal in the primary sensorimotor cortex increased withan increasing bite force in all subjects. These findings indicated the possibility of measuring the activated area in the primarysensorimotor cortex during clenching using functional magnetic resonance imaging, which revealed that the brain activity wasrelated to the magnitude of the bite force.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score0.278

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.000
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 head0.032
GPT teacher head0.284
Teacher spread0.252 · 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