A prototype ground penetrating radar system for soil characterization for the MIST 21-cm cosmology experiment
Bibliographic record
Abstract
High costs, alongside proprietary hardware and software act as a barrier to the widespread use of ground penetrating radar (GPR) technology in many areas of science, leaving an opening for an inexpensive open-source alternative which we will address. To this end, the initial design and prototyping of a low-cost GPR system for determining soil properties surrounding the Mapper of the Intergalactic Medium Spin Temperature (MIST) antenna is outlined. The MIST experiment observes globally averaged redshifted 21-cm emission from neutral hydrogen to constrain cosmic dawn. The instrument consists of a blade dipole antenna positioned above uncovered ground. Due to the lack of a backplane, the electrical properties of the soil surrounding the antenna must be known to a high degree of accuracy, necessitating the use of techniques such as GPR. Our GPR system is designed as an open-source, low-cost, light-weight unit that can withstand challenging environments and conditions. Our potential deployment regions include the Canadian Arctic, Deep Springs Valley in California, and Sarcobatus Flat in Nevada, where traditional soil survey methods face limitations. We have implemented the system using an Ettus Research USRP B210 software defined radio (SDR). The developed prototype GPR system uses stepped frequency continuous wave (SFCW) operation to synthesize an expanded bandwidth window compared to traditional SDR. Using a synthesized wide-band signal created from a series of stepped narrow-band chirps, we can create a system with tunable range and resolution. The prototype GPR system's hardware and software will be discussed in detail, along with the algorithm governing operation. We have conducted a series of field tests indicating satisfactory operation of the system, and placing some bounds on its ability to determine soil parameters. Outdoor tests taken on the McGill University campus show that we can constrain the overall underground soil structure, potentially distinguishing between basic one or two-layer soil models. Initial antenna simulations indicating the results of possible soil fluctuations on the global all-sky measurements taken by MIST are reported
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".