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Record W2367591871

Analyzing the Technical Strength of World Power Women Curling Teams

2010· article· en· W2367591871 on OpenAlexaboutno aff
Fan Yang

Bibliographic record

VenueChina Winter Sports · 2010
Typearticle
Languageen
FieldMedicine
TopicWinter Sports Injuries and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCurlingChampionshipWorld championshipComputer scienceMarketingBusinessEngineeringAdvertisingMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Starting with the delivery technique,with the methods of documentary information,consultation,observation and comprehensive analysis,taking the world three power women curling teams(the medalists—Sweden(gold),Canada(silver),and China(bronze)—of the 2010 Winter Olympics) as research objects,the paper has a statistical analysis on these teams' technical performances and basic tactical characteristics at 2009 world women curling championship,Pan-Pacific curling championship and European curling championship by using the correlative video information and the curling statistics software.The results show that Chinese team's delivery technique is well-drilled,Canadian team's slow delivery and protection skill stands out,Swedish team's cooperation reaches a tacit agreement by experience.The proportionality of delivery technique shows the high-level competitive character of modern curling.By understanding the power teams' delivery technique character,it puts forward a theoretical reference for working out the tactics and strategy of Chinese curling team.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.248
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), 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
Published2010
Admission routes1
Has abstractyes

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