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Record W1989174390 · doi:10.1080/02640410802475205

Relationships between stroke parameters and critical swimming speed in a sprint interval training set

2009· article· en· W1989174390 on OpenAlexaff
John M. Barden, Robert T. Kell

Bibliographic record

VenueJournal of Sports Sciences · 2009
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of AlbertaUniversity of Regina
Fundersnot available
KeywordsSprintStroke (engine)Anaerobic exerciseIntensity (physics)Critical speedPhysical medicine and rehabilitationMathematicsInterval trainingMedicineInterval (graph theory)Physical therapyPhysicsCombinatorics

Abstract

fetched live from OpenAlex

The aim of this study was to determine whether a relationship exists between stroke parameters and critical swimming speed (which is defined as the speed that can theoretically be maintained without exhaustion). Stroke parameters (stroke rate and length) and velocity were recorded for each 25-m length during a controlled sprint interval training set in which participants swam one of the four competitive strokes at a range of intensities below, at, and above critical speed. Eleven participants (8 females, 3 males; age 17.9 +/- 0.9 years) completed a progressive (descending) set of 8 x 100 m repetitions in a 25-m pool according to target times that ranged in intensity from 65% to 100% of the swimmer's best time (the intensity for each repetition increased by 5% throughout the set). The data showed that participants reached critical speed on the fourth repetition and that substantial and unpredictable changes in stroke parameters occurred once critical speed had been reached. Specifically, post-critical speed stroke rate and stroke length were significantly (P < 0.01) greater and less, respectively, than the pre-critical speed values, and these changes occurred in an abrupt and non-linear manner. Overall, the findings suggest that critical speed represents a transition point between two different sets of stroke parameter relationships--one for low-intensity aerobic swimming and one for high-intensity anaerobic swimming.

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)0.002
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 score0.026
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.153
GPT teacher head0.367
Teacher spread0.214 · 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

Citations40
Published2009
Admission routes1
Has abstractyes

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