MétaCan
Menu
Back to cohort
Record W2142155300 · doi:10.1115/imece2014-38767

Effect of Head Weight on the Biomechanics of a Cervical Spine Under Extension and Flexion Moments

2014· article· en· W2142155300 on OpenAlexafffund
Wissal Mesfar, Kodjo Moglo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsRoyal Military College of Canada
FundersMinistère de la Défense Nationale
KeywordsBiomechanicsKinematicsHead (geology)Facet (psychology)Parametric statisticsCervical spineFinite element methodOrthodonticsCervical vertebraeHead and neckAnatomyMedicineStructural engineeringEngineeringMathematicsGeologySurgeryPhysicsPsychology

Abstract

fetched live from OpenAlex

The determination of head and neck biomechanics is one of the keys for deep understanding of impairments in neck function and cervical spine pathologies. Finite element models are a valuable tool to perform parametric studies. In this study, we aim to investigate the effect of a 40N head weight on the biomechanics of the head and neck complex under flexion-extension moments. The loading is applied to the centre of mass of the head and the first thoracic vertebra is fixed. Our predictions show that the kinematics and the load distribution at the facet joints were altered significantly with considering of the head weight under the flexion and extension movements. Our investigations indicate the substantial role of the head weight on the biomechanical behavior of the cervical spine and suggest its consideration in comparing the models predictions with the measurements.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.300
Teacher spread0.281 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2014
Admission routes2
Has abstractyes

Explore more

Same topicAutomotive and Human Injury BiomechanicsFrench-language works237,207