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Record W3128100595 · doi:10.22374/jspv.v3i1.8

Gaze Behavior of Attacking Karate Athletes In-situ

2021· article· en· W3128100595 on OpenAlexvenueno aff
Nicole Bandow, Kerstin Witte

Bibliographic record

VenueJournal of Sports and Performance Vision · 2021
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsnot available
Fundersnot available
KeywordsGazeFixation (population genetics)AthletesPsychologyAdversaryComputer scienceComputer securityMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Previous studies have analyzed the gaze behavior of defending karate athletes using video-based attacks. The results show that karate athletes use a gaze anchor around the opponent’s head and chest. An analysis of gaze behavior of a karate athlete performing an attack in-situ has not been realized, yet. The aim of this study is, therefore, to analyze the gaze behavior of 11 karate athletes immediately before they perform an attack in-situ. The number of fixations, fixation duration, and fixation location were analyzed over the last 2000 ms before the athletes executed one of four instructed attacks. The results show no significant differ-ences in gaze parameters with respect to the type of attack. The main finding revealed a gaze anchor around the opponent’s head, chest, and leading arm, confirming previous studies of defending karate athletes whileviewing video-based attacks.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.022
GPT teacher head0.331
Teacher spread0.309 · 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.

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

Citations2
Published2021
Admission routes1
Has abstractyes

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