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Record W4293817437 · doi:10.3389/fphys.2022.899652

Time Course of Recovery Following CrossFit® Karen Benchmark Workout in Trained Men

2022· article· en· W4293817437 on OpenAlexaff
Ivo Vieira de Sousa Neto, Nuno Manuel Frade de Sousa, Frederico Ribeiro Neto, João Henrique Falk Neto, Ramires Alsamir Tibana

Bibliographic record

VenueFrontiers in Physiology · 2022
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSquatCreatine kinaseMedicinePhysical therapyPhysical medicine and rehabilitationInternal medicine

Abstract

fetched live from OpenAlex

The establishment of fatigue following the acute exercise stimulus is a complex and multi-factorial process, that might arise due to a range of distinct physiological mechanisms. However, a practical method of assessing CrossFit ® athletes’ recovery status has been neglected entirely in real-world sporting practice. The study describes the acute and delayed time course of recovery following the CrossFit ® Benchmark Workout Karen. Eight trained men (28.4 ± 6.4 years; 1RM back squat 139.1 ± 26.0 kg) undertook the Karen protocol. The protocol consists of 150 Wall Balls (9 kg), aiming to hit a target 3 m high. Countermovement jump height (CMJ), creatine kinase (CK), and perceived recovery status scale (PRS) (general, lower and upper limbs) were assessed pre, post-0h, 24, 48 and 72 h after the session. The creatine kinase concentration 24 h after was higher than pre-exercise (338.4 U/L vs. 143.3 U/L; p = 0.040). At 48h and 72 h following exercise, CK concentration had returned to baseline levels ( p > 0.05). The general, lower and upper limbs PRS scores were lower in the 24-h post-exercise compared to pre-exercise (general PRS: 4.7 ± 1.5 and 7.7 ± 1.7; p = 0.013; upper limbs PRS: 6.6 ± 1.3 and 7.5 ± 1.3; p = 0.037; lower limbs PRS: 3.9 ± 2.5 and 7.3 ± 0.1; p = 0.046). Our findings provide insights into the fatigue profile and recovery in acute CrossFit ® and can be useful to coaches and practitioners when planning training programs. Moreover, recovery status can be useful to optimize training monitoring and to minimize the potential detrimental effects associated with the performance of repeated high-intensity sessions of CrossFit ® .

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 score0.073
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.008
GPT teacher head0.250
Teacher spread0.242 · 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

Citations20
Published2022
Admission routes1
Has abstractyes

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