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Record W2109415438 · doi:10.1243/17543371jset29

Effects of ice hockey facial protectors on the response time and kinematics in goal-directed tasks

2009· article· en· W2109415438 on OpenAlexafffund
Patrick M. Dowler, David J. Pearsall, Paul J. Stapley

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part P Journal of Sports Engineering and Technology · 2009
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsKinematicsIce hockeyComputer sciencePhysical medicine and rehabilitationSimulationTask (project management)PsychologyArtificial intelligenceMedicineEngineeringPhysics

Abstract

fetched live from OpenAlex

Ice hockey facial protectors are essential to prevent eye (and, in some cases, dental) injuries but must also not encumber vision and, in turn, playersapos; performance. The purpose of this study was to investigate the effects of three different facial protection conditions on temporal and kinematic parameters in a goal-directed pointing task: helmet (control), visor, and cage. Start and end target switches captured temporal estimates (reaction time (RT), movement time, (MT), and response time (RT+MT)), while a 13-light target array and 6-camera Vicon Mx system were used to collect upper-body kinematics data (head and thorax orientation, shoulder and elbow joint angles). Subjects recruited were 16 male and 12 female varsity ice hockey players ( n=28). Results demonstrated that, although kinematics remained largely unaffected, throughout the target array RTMT increased significantly with the cage (23 ms) as well as delayed initiation of head rotation for both the visor (14 ms) and the cage (18 ms). These differences may well represent a functional disadvantage to a player's performance given the dynamic open environment where multiple players contest for puck possession. It must be stressed that facial protectors still provide an effective form of protection and thus should still be worn at all levels of play. In summary, further research is warranted to achieve both optimal performance and 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.

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)0.002
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0030.000

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 head0.004
GPT teacher head0.201
Teacher spread0.198 · 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

Citations4
Published2009
Admission routes2
Has abstractyes

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Same venueProceedings of the Institution of Mechanical Engineers Part P Journal of Sports Engineering and TechnologySame topicSports injuries and preventionFrench-language works237,207