A canonic tunable RC notch filter with adjustable selectivity
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Bibliographic record
Abstract
Null networks are widely used in audio and instrumentation systems not only for eliminating undesired frequencies and for measuring transient harmonic distortion (THD) but also as central components of selective filters and oscillators in feedback arrangements. Of the various three-terminal notch filters and four-terminal selective bridge circuits in use, the RC twin-tee is perhaps the best known and most widely utilized. However, as certain relations have to be maintained between the various elements (minimum six) of these networks, they are not readily tunable and independent control of selectivity is also rather difficult. Thus, the twin-tee structure is essentially suited to fixed-frequency operation. The purpose of this study is to explore canonic second-order RC structures with four elements that are easily tunable and whose selectivity can also be varied independently and conveniently. A practical realization of the feedback and feedfoward arrangements proposed is given.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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 | 0.001 |
| Open science | 0.000 | 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 it