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Record W4391363634 · doi:10.22514/jomh.2024.003

The level of the aggression in karate athletes with different handedness and belt grades

2024· article· en· W4391363634 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

VenueJournal of Men s Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Training Studies
Canadian institutionsCanadian Society for Exercise Physiology
Fundersnot available
KeywordsAthletesAggressionPsychologyDevelopmental psychologyPhysical therapyMedicine

Abstract

fetched live from OpenAlex

Karate athletes with different lateral talents possess different functions in terms of skills and personality characteristics in a way that handedness can be considered an advantage. Given that there is a paucity of research in the domain of personality characteristics, handedness and belt grades, the current research aims to investigate the relationship between handedness and belt grades with aggression among karate athletes. 120 male karate athletes participated. To measure handedness, we used Annette’s handedness questionnaire and to measure aggression, we used Bredemeier’s aggression questionnaire. The questionnaires were distributed among participants one day before the tournament. A two-way analysis of variance (ANOVA) was used to measure the effects of belt grades and handedness on the level of aggression. The results of the study indicated that there was no statistically significant difference in the average level of aggression between left-handed and right-handed karate athletes. There was also no statistically significant difference in the average level of aggression between karate athletes with different belt grades.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.699
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.182
GPT teacher head0.479
Teacher spread0.297 · 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