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Record W2616842997

Shooting side orientation and elite performance in ice hockey

2010· article· en· W2616842997 on OpenAlexaff
Jared Puterman, Jörg Schorer, Joseph Baker

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsYork University
Fundersnot available
KeywordsLateralityIce hockeyLeaguePsychologyEliteCompetition (biology)Physical medicine and rehabilitationDevelopmental psychologyMedicinePolitical science
DOInot available

Abstract

fetched live from OpenAlex

Little is known regarding the implications of motor asymmetries for skilled performers in dynamic, time-constrained, team-based activities such as ice hockey. Two studies were conducted to examine laterality differences in ice hockey. Study one investigated laterality distributions across three leagues of increasing league calibre. Among skating players, skill level was related to changes in laterality patterns based on position, while a significant increase in the proportion of left catching goaltenders was found across the levels of competition. Study two examined laterality differences through a 90-year retrospective analysis of player performance measures within an evolving system. Regression analysis indicated right shot preferences were associated with scoring more goals, while left shot preferences were related to assisting more goals. Among goaltenders, right catching preferences were associated with an increased save percentage compared to left-catching goaltenders. Results suggest ice hockey supports models of skilled perception, and provides new information in the area of laterality and strategic frequency-dependent effects in ice hockey.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.269
Teacher spread0.252 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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