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Record W1973273091 · doi:10.1055/s-0033-1353141

Acute Hormonal Responses Before and After 2 Weeks of HIT in Well Trained Junior Triathletes

2013· article· en· W1973273091 on OpenAlexaff
Christoph Zinner, Patrick Wahl, Silvia Achtzehn, Jennifer L. Reed, Joachim Mester

Bibliographic record

VenueInternational Journal of Sports Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineAnabolismHormoneTestosterone (patch)Session (web analytics)Internal medicinePhysical therapy

Abstract

fetched live from OpenAlex

The aim was to compare the acute hormonal response to a single HIT session at the beginning and end of a HIT shock microcycle. 13 male junior triathletes (15.8±1.8 yrs.) performed 16 HIT sessions within a 2 week period. Venous blood samples were collected before and after the first and last HIT session. Significant increases in cortisol (first session +89.7%; last session +70.3%) and hGH (first session +435.1%; last session +314.6%) concentrations were observed after both training sessions (P<0.05). The acute responses of cortisol, hGH, T3, and fT3 were not different between the first and last HIT sessions (P=1.00). Although no acute changes in testosterone were detected after the training sessions, testosterone concentrations were significantly higher at all time points (62.6-80.1%) during the last compared to first training session (P≤0.001). Findings from the present study reveal that 16 sessions of HIT led to significant increases in baseline concentrations of serum testosterone. This might indicate a heightened anabolic state even in junior triathletes. Based on the hormonal data, we conclude that at the end of this 2 week microcycle no familiarization effect was evident and that the training stimulus produced by HIT was still great enough to "stress" the athletes and induce positive training adaptations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.283
Teacher spread0.274 · 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.

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

Citations33
Published2013
Admission routes1
Has abstractyes

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