Heart Rate Responses at Onset of Contraction
Bibliographic record
Abstract
We tested the hypothesis that the initial heart rate (HR) response at the onset of maximal handgrip contraction is altered after training. 17 volunteers (nine trained and eight controls) performed ten intermittent static handgrip contractions with maximal effort, alternating between 15-s contractions and 15-s pauses. High-intensity static handgrip training was performed using the nondominant arm alone for 4 weeks. Handgrip force (HGF) and HR were analyzed for the initial 7 s of every static handgrip exercise. Peak HR (pre-training: 94.5 +/- 12.8 beats/min; post-training: 89.7 +/- 10.2 beats/min, p < 0.05) decreased. However, the magnitude of HR change at the onset of contraction remained constant (pre-training: 23.0 +/- 7.7 beats/min; post-training: 25.7 +/- 6.5 beats/min, p = 0.0767), while the HR responses in the subsequent bouts increased after training (p < 0.001). The resting HR decreased (pre-training: 71.5 +/- 9.3 beats/min; post-training 64.1 +/- 5.7 beats/min, p < 0.05). Maximal HGF increased by 11.1 % in trained arms and by 8.7 % in untrained arms, although an increase in maximal forearm girth was only observed in the trained arm (2.0 %, p < 0.0001). Although high-intensity training modulated the abrupt HR responses, the magnitude of the response remained unchanged at the onset of maximal forearm contraction and the resting HR significantly decreased.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".