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Record W3135270940 · doi:10.1123/jab.2020-0070

The Influence of Neck Stiffness on Head Kinematics and Maximum Principal Strain Associated With Youth American Football Collisions

2021· article· en· W3135270940 on OpenAlexaff
Janie Cournoyer, David Koncan, Michael D. Gilchrist, T. Blaine Hoshizaki

Bibliographic record

VenueJournal of Applied Biomechanics · 2021
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHybrid IIIKinematicsStiffnessOrthodonticsStructural engineeringHead (geology)PercentileStrain (injury)AccelerationPhysical medicine and rehabilitationPoison controlMathematicsMedicineGeologyAnatomyPhysicsEngineeringStatistics

Abstract

fetched live from OpenAlex

Understanding the relationship between head mass and neck stiffness during direct head impacts is especially concerning in youth sports where athletes have higher proportional head mass to neck strength. This study compared 2 neck stiffness conditions for peak linear and rotational acceleration and brain tissue deformations across 3 impact velocities, 3 impact locations, and 2 striking masses. A pendulum fitted with a nylon cap was used to impact a fifth percentile hybrid III headform equipped with 9 accelerometers and fitted with a youth American football helmet. The 2 neck stiffness conditions consisted of a neckform with and without resistance in 3 planes, representing the upper trapezius, the splenius capitis, and the sternocleidomastoid muscles. Increased neck stiffness resulted in significant changes in head kinematics and maximum principal strain specific to impact velocity, impact location, and striking mass.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

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)0.0010.000

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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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 designBench or experimental
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

Citations6
Published2021
Admission routes1
Has abstractyes

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