Endurance Running Training Individually Guided by HRV in Untrained Women
Why this work is in the frame
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Bibliographic record
Abstract
da Silva, DF, Ferraro, ZM, Adamo, KB, and Machado, FA. Endurance running training individually guided by HRV in untrained women. J Strength Cond Res 33(3): 736-746, 2019-The aim of this study was to analyze the effects of heart rate variability (HRV)-guided training compared with a standardized prescription on (a) time to complete 5-km running performance (t5km), (b) peak treadmill running speed (Vpeak) and its time limit (tlim at Vpeak), and (c) autonomic cardiac modulation (i.e., parasympathetic activity and recovery) in untrained women. Additionally, we correlated changes in t5km with changes in Vpeak, tlim at Vpeak and autonomic cardiac modulation. Thirty-six untrained women were divided into a HRV-guided training group (HRVG) and a control group (CG). The CG followed a predefined program, alternating moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT). The determination of MICT or HIIT was based on the pretraining HRV for HRVG. MICT was performed if HRV was <mean - 1 SD of previous measures. Otherwise, HIIT was prescribed. The t5km, Vpeak, tlim at Vpeak, parasympathetic activity (i.e., rMSSD) and parasympathetic reactivation (i.e., HRR) were measured before and after the training period. The t5km decreased to a greater magnitude in the HRVG (-17.5 ± 5.6% vs. -14 ± 4.7%; Effect Size (ES) between-group difference = moderate). rMSSD and tlim at Vpeak only improved in HRVG (+23.3 ± 27.8% and +23.6 ± 31.9%, respectively). The HRVG experienced greater improvements in Vpeak and HRR (Vpeak: 10 ± 7.3% vs. 8.2 ± 4.7%; HRR: 19.1 ± 28.1% vs. 12.6 ± 12.9%; ES between-group difference = small). Although HRVG performed less MICT than CG, the volume of MICT was negatively related to changes in t5km. Vpeak changes were highly correlated with t5km changes. The greater improvements in HRVG for t5km and autonomic modulation reinforce the potential application of this tool.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it