The Effect of the Menstrual Cycle on Daily Measures of Heart Rate Variability in Athletic Women
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract. Heart rate variability (HRV) is a biomarker used to reflect both healthy and pathological state(s). The effect of the menstrual cycle and menstrual cycle phases (follicular, luteal) on HRV remains unclear. Active eumenorrheic women free from exogenous hormones completed five consecutive weeks of daily, oral basal body temperature (BBT) and HRV measurements upon waking. Descriptive statistics were used to characterize shifts in the HRV measures: standard deviation of NN intervals (SDNN), root mean square of successive difference (rMSSD), high (HF) and low frequency (LF) across the menstrual cycle and between phases. All HRV measures were assessed by medians ( Mdn), median difference of consecutive days ( Mdn∆) and variance. Seven participants ( M ± SD; age: 28.60 ± 8.40 year) completed the study with regular menstrual cycles (28.40 ± 2.30 days; ovulation day 14.57 ± 0.98 day). Median rMSSD displayed a nonlinear decrease across the menstrual cycle and plateau around the day of ovulation. A negative shift before ovulation in Mdn∆, rMSSD, SDNN, and LF as well as peak on luteal phase Day 4 in rMSSD and SDNN was observed. Median variance increased in rMSSD (150.06 ms 2 ) SDNN (271.12 ms 2 ), and LF variance (0.001 sec 2 /Hz) from follicular to luteal phase. Daily HRV associated with the parasympathetic nervous system was observed to decrease nonlinearly across the menstrual cycle.
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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 | 0.004 | 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 | 0.000 |
| 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