Linear and nonlinear approaches in processing of neurophysiological data: biomedical and mathematical principles
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
The diagnostic relevance and practical utility of traditional ways related to biomedical signal processing is often questionable.Traditional power spectral analysis was not designed for complex nonstationary EEG and other neurophysiological recordings with nonlinear nature.As brain activity is a highly complex and irregular system, we highlight a more suitable measures of multiple timefrequency resolution, especially the wavelet analysis, chaos theory and methods of nonlinear dynamics.Those non-conventional approaches proved a high sensitivity for the diagnosis of different neurophysiological stages.In this paper, we present algorithms to quantify the neurophysiological data complexity and discuss their practical relevance and diagnostic potential.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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