Autonomic recovery following sprint interval exercise
Bibliographic record
Abstract
The autonomic nervous activity was assessed following supramaximal exercise through heart rate (HR) and blood pressure (BP) variability (HRV and BPV) and baroreflex sensitivity (BRS). The beat-to-beat HR and BP were recorded during the supine and standing states before (PRE) and at 60 (R60) and 120 min (R120) following single (one Wingate, 1W) and multiple sprint intervals (four Wingates interspersed with 4 min of light cycling, 4W). The supine low frequency (LF) component was increased (P<0.001) and the high frequency (HF) was reduced (P<0.01) at R60 (LF, 178.1 ± 11.0; HF, 74.8 ± 10.5) compared with PRE (LF, 140.2 ± 7.4; HF, 110.4 ± 7.2) after both exercises. Supine systolic BPV LF:HF was higher at R60 (4.6 ± 1.4) compared with PRE (6.8 ± 2.4) only after 4W (P=0.035). Supine BRS was lower (P<0.001) at R60 (6.8 ± 1.1) than at PRE (15.3 ± 1.8) and R120 (11.3 ± 1.3). BRS at R120 remained lower after 4W (P=0.02). Standing BRS was less (P<0.001) at R60 (2.3 ± 0.5) than at PRE (5.6 ± 0.8) or R120 (3.7 ± 0.6) and returned to PRE values only after 1W. We concluded that (a) autonomic balance is shifted to a greater sympathetic and less parasympathetic activation following both types of exercise, (b) it takes longer than 1 h to recover following supramaximal exercise and (c) the recovery is longer after 4W than 1W.
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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".