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Record W2161325585 · doi:10.1080/10255842.2011.627559

Examination of the relationship between peak linear and angular accelerations to brain deformation metrics in hockey helmet impacts

2011· article· en· W2161325585 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

VenueComputer Methods in Biomechanics & Biomedical Engineering · 2011
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAngular accelerationAccelerationLinear accelerationDeformation (meteorology)Ice hockeyLinear relationshipPoison controlPhysical medicine and rehabilitationConcussionSimulationComputer scienceInjury preventionMathematicsPhysicsMedicineStatisticsMeteorologyMedical emergencyClassical mechanics

Abstract

fetched live from OpenAlex

Ice hockey is a contact sport which has a high incidence of brain injury. The current methods of evaluating protective devices use peak resultant linear acceleration as their pass/fail criteria, which are not fully representative of brain injuries as a whole. The purpose of this study was to examine how the linear and angular acceleration loading curves from a helmeted impact influence currently used brain deformation injury metrics. A helmeted Hybrid III headform was impacted in five centric and non-centric impact sites to elicit linear and angular acceleration responses. These responses were examined through the use of a brain model. The results indicated that when the helmet is examined using peak resultant linear acceleration alone, they are similar and protective, but when a 3D brain deformation response is used to examine the helmets, there are risks of brain injury with lower linear accelerations which would pass standard certifications for safety.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.583
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
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 head0.096
GPT teacher head0.358
Teacher spread0.262 · 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