Application of bit error rate monitoring to differential detection of MSK, QPSK, OQPSK and DUOMSK signals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The pseudoerror method based on amplitude threshold variation is applied to differential detection of QPSK (quaternary phase-shift keying), OQPSK (offset QPSK), DUOMSK (duobinary minimum-shift keying), and MSK signals. The objective of this differential-detection estimation was to reduce the simulation time required for bit-error-rate estimation relative to the Monte Carlo method. The gain in simulation time obtained in this way was shown in a specific case to be on the order of 5.5 and 8.7 for amplitude thresholds of 10 and 15%. The small approximation error values of the order of 0.1 to 0.4 dB obtained with these thresholds lead to the conclusion that the method gives very good results, permitting performance estimates for bit error rates smaller than 10/sup -4/.< <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 | 0.000 |
| 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