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Record W2186338058

A profile of olympic taekwondo competitors.

2006· article· en· W2186338058 on OpenAlexaff
Mohsen Kazemi, Judith Waalen, Chris Morgan, Anthony R. White

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsAthletesOffensiveDemographyBody mass indexMedicinePhysical therapyMathematicsOperations researchInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to identify the profile of the Olympic champions and the other competitors who were involved in the Games. The information on each of the athletes was obtained from the "Official Site of the Sydney 2000 Olympic Games, www.olympics.com/eng/sports/TK "and included weight category, weight, height, age, points obtained, warnings, deduction point, defensive/offensive kicks and punches. One hundred and two athletes competed (54 males and 48 females) in the Games. The mean average age and BMI (Body Mass Index) of 16 male winners was 24.4 ± 3.3 years and 21.9 ± 2.4 respectively compared to 25.2 ± 4.3 years and 22.8 ± 3.3 for the 38 male non-winners. The mean average age and BMI of the 16 female winners was 23.1 ± 3.9 years and 20.8 ± 2.3 respectively compared to 24.9 ± 4.7 years and 21.3 ± 2.7 for the 32 female non-winners. For all four types of athletes, offensive kicks accounted for at least 52% of the techniques to score a point. Ninety-eight percent of all techniques used to score were kicks. Although not statistically significant, winners overall tended to be younger in age and taller with slightly lower BMI than their weight category average. Taking into account the literature cited in this article, future studies should be designed to examine the relationship between performance and functional variables such as muscle power, muscle endurance, reaction time and aerobic capacity. Key PointsWinners tended to be younger in age and taller with slightly lower BMI than their weight category average.An offensive technique was used to score slightly more often than a defensive one.Overall, 98% of all techniques used to score were kicks.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.330

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)0.0000.000

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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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 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

Citations122
Published2006
Admission routes1
Has abstractyes

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