Bibliographic record
Abstract
During the performance evaluation of 3-phase control systems synchronization in real time, it is useful to synthesize test signals with modulated characteristics, such as frequency, phase, un-balancing, distortion, notching, and random noise. The principles and structure of a proposed generic program in the C language are presented, which can be easily adapted and compiled for any target DSP platform. The proposed structure offers such advantages as the ability to easily create a precompiled library of elementary, re-usable, building blocks, which can subsequently be easily "inter-connected", equivalently as it would be done physically; these connections can easily be re-configured at run time, allowing for variable operating parameters; the actual application coding can then be greatly simplified. In contrast to graphical design programs and object oriented languages, which often serve a limited number of target processors and reduce the efficiency of the compiled program with significant additional overhead code, the proposed approach is accomplished in the C language, using elementary constructs such as structures, variable and function pointers. An example application program is presented, as well as representative synthesized waveforms
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".