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Record W2383249330

Actual strength of Korean Short Track Women's Team at the Vancouver Winter Olympics in 2010

2009· article· en· W2383249330 on OpenAlexaboutno aff
Cai Lan

Bibliographic record

VenueJournal of Shandong Institute of Physical Education and Sports · 2009
Typearticle
Languageen
FieldMedicine
TopicWinter Sports Injuries and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCompetition (biology)Training (meteorology)Track (disk drive)ObstacleBusinessAdvertisingMarketingPolitical sciencePsychologyGeographyEngineeringLaw
DOInot available

Abstract

fetched live from OpenAlex

In order to explore the strength of the South Korean women's team of short-track skating that participate in the Vancouver Winter Olympic Games,it mainly used the ways of literature and video observation to analyze the situation of the training characteristics,and the performance of the new Korean women's team in major international competitions hosted by ISU at the last three years.The results showed that: 1) The selection match of South Korea national team is organized very well,highly competitive,and reflecting the competition purposes of fair and impartial,which is conducive to sustainable development of short-track speed skating.2) The new members inherit the older members' features;most of the members have a strong long-range power,while the short-range strength is weaker.3) South Korea team members' training load is heavy,and the training is targeted.South Korea women's team is still a major obstacle to Chinese at the Vancouver Winter Olympics.Recommendations: Takeing advantage of the opportunity that South Korea are training overseas in July,we should do a good job on the research of South Korea and take specific countermeasures.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.267

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 head0.007
GPT teacher head0.272
Teacher spread0.265 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

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