Interpreting power-spectral-measures extracted from sympathetic nerve activity: possibilities and pitfalls
Bibliographic record
Abstract
This paper discusses the possibilities and potential pitfalls associated with interpretations based on the low-frequency power (LFP), the high-frequency power (HFP) and their ratio: PR=LFP/HFP, computed from muscle sympathetic nerve activity (MSNA). Segments of MSNA from several subjects were analyzed by Capon's minimum variance distortionless response (MVDR) method. The power spectra revealed peaks within [0-0.5] Hz, apart from the peak at the cardiac-related frequency (CF). Our investigations reveal that: (1) the presence of nearly periodic (groups of) bursts can produce strong harmonics that affect the HF component and hence the accuracy of HFP and PR, (2) changes in the strong CF-component can affect the components within the lower frequency range, and (3) small changes in the location of the needle electrode can affect the spectral-measures.
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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 | 0.038 | 0.179 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".