Analysis of Waveshape and Waveform Complexity
Bibliographic record
Abstract
Certain biomedical signals, such as the electrocardiogram (ECG) and the carotid pulse, have simple waveshapes. The readily identifiable signatures of the ECG and the carotid pulse are modified by abnormal events and pathological processes. Hence, analysis of waveshapes could be useful in the diagnosis of various diseases. Signals such as the electromyogram (EMG) and the phonocardiogram (PCG) do not have waveshapes that may be identified easily. EMG signals are complex interference patterns of innumerable single-motor-unit action potentials. PCG signals represent vibration waves that do not possess specific waveshapes. Regardless, even the complexity of the waveforms in some signals, such as the EMG and the PCG, does vary in relation to physiological and pathological phenomena. The problem statement given is generic and represents the theme of the present chapter. The chapter presents illustrations of the problem with case studies that provide more specific definitions of the problem with a few signals of interest.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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 teacher head, 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".