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Record W2079631798 · doi:10.1080/10578310210398

Time Motion Analysis and Physiological Profile of Canadian World Cup Wheelchair Basketball Players

2001· article· en· W2079631798 on OpenAlexaffabout
Lara A. Bloxham, Gordon J. Bell, Yagesh Bhambhani, Robert D. Steadward

Bibliographic record

VenueSports medicine, training, and rehabilitation/Sports medicine, training and rehabilitation · 2001
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBasketballWheelchairMotion (physics)Motion analysisPhysical medicine and rehabilitationAeronauticsPsychologyComputer scienceGeographyEngineeringArtificial intelligenceMedicineWorld Wide Web

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate the time elite wheelchair basketball players spent performing various game activities during a World Cup game, measure the heart rate response during such activity, and describe the physiological profile of each player participating in the game. Six male members of the Canadian World Cup wheelchair basketball team were videotaped during an entire game to determine the time spent performing seven different categories of activity. Time motion analysis indicated that players spent 8.9% of the game time sprinting, 23.5% gliding, 18.2% contesting for ball possession, 0.6% sprinting with the ball, 0.3% shooting, and 48.3% resting on the bench and floor. Twenty percent (20%) of game time was played at an intensity above the ventilatory threshold. The group mean value for peak oxygen uptake during incremental wheelchair exercise on rollers was 2.60L/min and group mean peak 5 and 30 second anaerobic power development on an arm crank ergometer was 486.3 W and 336.8 W, respectively, suggest that training for and playing elite wheelchair basketball induces significant improvement in these tests of fitness.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.654
Threshold uncertainty score0.688

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.269
Teacher spread0.247 · 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

Citations66
Published2001
Admission routes2
Has abstractyes

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