Bibliographic record
Abstract
In this work, we employed the XeThru X4M300 radar to generate and receive Ultra-Wideband (UWB) signals for human activity recognition in indoor environments. The XeThru X4M300 pulse-Doppler radar module operates at a configurable carrier frequency of either 7.29 GHz or 8.42 GHz, providing a high-resolution solution specifically suited to indoor applications such as human presence monitoring, motion tracking, and security. Its UWB pulse transmission enables enhanced range resolution, crucial for accurately distinguishing between multiple human activities. Key attributes of X4M300 radar include its adaptability for customized settings, such as adjustable detection range, frame rate, pulse count per step, and sweep iteration. These configurable parameters allow precise optimization for various applications, maximizing signal clarity and robustness. Additionally, the radar module is equipped with digital down-conversion, advanced filtering, and data rate optimization capabilities, enhancing both signal processing efficiency and data fidelity, which are essential in radar-based human activity recognition tasks where real-time, high-quality data capture is critical.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.068 |
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".