Bibliographic record
Abstract
In this dataset, Signal of Interest (SoI) is a real-time video stream that is transmitted using DVB-S2 standards in four modulation types including (QPSK, 8/16/32 APSK). Further, this SoI combined by three well-known jamming signals namely, Continuous Wave Interference (CWI), Multiple CWI (MCWI), and Chirp Interference (CI). This dataset includes 300 samples per modulation type for each type of signal. Therefore, totally there are 4800 samples in the dataset and each sample is a vector of size 1 by 32488 (8ms) at sample frequency 40 Hz. Also, AWGN power is -140 dBm which is approximately equal to SNR=9 dB. More importantly, SoI is modulated and processed by GNU radio and transmitted using a Universal Software Radio Peripheral (USRP-N210). In GNU radio, the modulation type and amplitude of the transmitted signal can be easily adjusted. A SatCom Emulator (RTLogic T400) is used for modeling a real-time communication channel. The programmatic control of the channel simulator is facilitated over an Ethernet connection using a control protocol or optional plugin to STK software. The Channel Simulator produces IF/RF signals with extracting signal characteristics for any scenario. The Kratos STK plugin provides real-time, phase-continuous control of the channel simulator when playing STK scenarios. Further, the generated jamming signals (CWI, MCWI, and CI) are transmitted using a NanoBee modem and combined to SoI by a combiner. Finally, the combined signal is received by a MegaBee modem. Notably, in this dataset, each jammer indicates a combination of SoI with that jammer, as an instance "CWI_16APSK " refers to SoI (16APSK)+CWI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.020 |
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".