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
Several models have been proposed for the simulation of Rayleigh fading channels. However, existing simulators lack to properly consider the correlation between the subchannels of an OFDM system. We use a recently developed cross-correlation function that describes both temporal and frequency correlation in order to generate channel parameters. This correlation function is decomposable into multiplication of two correlation functions. The first term characterizes only the temporal correlation and the other characterizes the correlation between subchannels. Using this property, the proposed simulator is implemented in cascade of two steps. In the first step, we propose an improved IFFT method for generation of multiple independent temporally correlated complex Gaussian processes following the given temporal correlation. We then transform these processes into a vector random processes by a transformation which is obtained by factorization of the frequency-correlation matrix. Our results reveal that the proposed technique accurately generates the desired statistical properties. This method is efficient in terms of computation complexity and runtime cost.
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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 | 0.001 | 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 it