Comparison of GPR signals over simulated clandestine graves with domestic pigs (<i>Sus Scrofa domesticus</i>) and human remains
Why this work is in the frame
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Bibliographic record
Abstract
Studies assessing the use of ground-penetrating radar (GPR) for locating unmarked human graves commonly use pigs as proxies, with recent concerns about the adequacy of pigs as substitutes for humans. Also, there is little agreement on how to identify and describe GPR signals associated with graves. Hence, this project's aim is to compare GPR signals acquired over simulated clandestine graves with pig and human remains. We established human, pig, and control graves at the REST[ES] human decomposition facility in May 2022 and monitored the graves over 17 months using a 250 MHz antenna GPR system. Our results showed the presence of perturbed and V-shaped reflectors, diffraction hyperbolas, and reflectors with amplitude loss at depth between 0.6 and 0.75 m in the radargram for graves with human and pig remains. We corroborate recent studies which concluded that the use of proxies is a viable alternative to human cadavers. The observed radar signatures were classified into five key patterns, which are characteristic of similar data collected with 250 MHz above graves reported in the literature. These classes are: V-shaped dipping reflections from grave walls (class A), small hyperbolic reflections superimposed onto a near-linear reflector (class B), hyperbolic reflections from remains within the grave (class C), new high-amplitude reflection patterns (class D) and significant loss or interruption of reflections (class E). Our proposed classification can help streamline future investigations where the goal is to interpret burials within large GPR datasets and provide language to communicate these results to the broader scientific community.
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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 | 0.001 |
| 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