SYSEG — Symbolic state equation generation
Bibliographic record
Abstract
One of the most important goals for this study is to reveal an effective way to develop systematically the state equations that define the analog circuits (linear, non-linear, timeinvariant etc.) with excess elements. These equations can be depicted in various forms, like symbolic form, numeric-symbolic form, numeric-normal form. At the beginning, we designed the calculation method and afterwards we built the computer application, named SYSEG (SYSEG — Symbolic State Equation Generation), this software being able to obtain the normal form of the state equations. SYSEG does not calculate any inverse matrix, succeeding to get the compact form of the state equations through subsequent abridgements of the mathematic expressions. The first kind degeneracies are resolved in a unitary way in order to support the symbolic form to use a small number of state variables. The SYSEG application can work with circuits that have in their structure elements like: all types of linear controlled sources, independent sources (voltage and current), linear and non-linear resistors, capacitors and inductors. Also, this software is a very efficient instrument to be used for the symbolic analysis and for the circuits design (linear/non-linear time-invariant analog circuits).
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 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".