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Record W799926894 · doi:10.1520/stp15231s

Comparison of Ice Hockey Helmet Impact Attenuation Tests on Steel and Elastomeric Impact Surfaces

2000· book-chapter· en· W799926894 on OpenAlexaff
J Sabelli, CA Morehouse

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsIntertek (Canada)
Fundersnot available
KeywordsIce hockeyElastomerAttenuationForensic engineeringImpactMaterials scienceComposite materialStructural engineeringEngineeringPhysical medicine and rehabilitationMedicinePhysicsOptics

Abstract

fetched live from OpenAlex

United States ice hockey helmet standards were developed with an elastomeric surface for impact attenuation tests. These tests measure peak acceleration as a function of impact velocity. Recently, other standards have specified a flat steel impact surface, with a lower impact velocity (3.96 m/s as opposed to 4.50 m/s) to compensate for the greater hardness of the surface. It has been proposed that the U.S. standard be revised to use the steel impact surface, with the lower impact velocity. A series of tests was conducted to determine whether tests performed with the proposed lower impact velocity on steel would yield peak acceleration results equivalent to test results with the higher impact velocity on an elastomeric surface. Tests were performed on three different models of ice hockey helmets. Impact tests were conducted at 4.50 m/s on the elastomeric surface, 3.96 m/s on steel, and 4.20 m/s on steel. Results are compared for the three impact schemes.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.104
GPT teacher head0.422
Teacher spread0.318 · 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

Citations0
Published2000
Admission routes1
Has abstractyes

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