Chaos Criteria Design Based on Modified Sign Functions with One or Three‐Threshold
Why this work is in the frame
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Bibliographic record
Abstract
The complexity measures of chaotic or periodic signals are perpetual topics of interest to data scientists. This work adheres to the framework of the traditional 0-1 test for chaos and replaces sine and cosine functions by modified sign functions. The compressive mapping rules chosen are one-threshold of three-value or three-threshold of five-value. In new criteria for chaos in forms of the 3s plot and Ks metric compared with 0-1 test results, the periodic state of data features a short beeline instead of a big ring in the pq plot and signs the nearest zero mark, while the chaotic state signs a simple curve instead of a random-walking shape in the pq plot, and shows the nearest one mark. By computing the Lorenz equation evolution under the contrast tests of the Poincare section and Lyapunov index, we visualize a new chaoscriteria design in symbolic dynamics and data compression principles, and our work may lay the foundation for further expressing the chaotic appearance of novel signals deep into future brainets.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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