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Record W2140901411 · doi:10.1177/1754337112448765

The application of brain tissue deformation values in assessing the safety performance of ice hockey helmets

2012· article· en· W2140901411 on OpenAlexaff
T. Blaine Hoshizaki, Evan S. Walsh, Andrew Post, Philippe Rousseau, Marshall Kendall, Clara Karton, Anna Oeur, Scott Foreman, Michael D. Gilchrist

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part P Journal of Sports Engineering and Technology · 2012
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsImpactOntario Neurotrauma FoundationUniversity of Ottawa
Fundersnot available
KeywordsIce hockeyConcussionTraumatic brain injuryAngular accelerationLinear accelerationAccelerationBrain traumaDeformation (meteorology)Physical medicine and rehabilitationPoison controlHead (geology)Brain tissueComputer scienceInjury preventionEngineeringGeologyMedicinePhysicsBiomedical engineeringMedical emergencyMeteorology

Abstract

fetched live from OpenAlex

This research was undertaken to examine a new method for assessing the performance of ice hockey helmets. It has been proposed that the current centric impact standards for ice hockey helmets, measuring peak linear acceleration, have effectively eliminated traumatic head injuries in the sport, but that angular acceleration and brain tissue deformation metrics are more sensitive to the conditions associated with concussive injuries, which continue to be a common injury. Ice hockey helmets were impacted using both centric and non-centric impact protocols at 7.5 m/s using a linear impactor. Dynamic impact responses and brain tissue deformations from the helmeted centric and non-centric head form impacts were assessed with respect to proposed concussive injury thresholds from the literature. The results of the helmet impacts showed that the method used was sensitive enough to distinguish differences in performance between helmet models. The results have shown that peak linear acceleration yielded low magnitudes of response to an impact, but peak angular acceleration and brain deformation metrics consistently reported higher magnitudes, reflecting a high risk for incurring a mild traumatic brain injury.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.248
Teacher spread0.241 · 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 teacher head, 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

Citations10
Published2012
Admission routes1
Has abstractyes

Explore more

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