Experimental use of pig cadavers to locate homicide victim in a large river
Bibliographic record
Abstract
The transport of full body human remains in fluvial environments has few published examples to guide recovery efforts. The decomposition stage, flow environment, water temperature and river morphology can all interact to affect the rate and distance deceased human bodies will travel, and case studies or experimental efforts are rare. In this case report, we provide an experimental deployment of pig carcasses to emulate a real homicide event where a body was dropped into a large 7th order Northern Great Plains river to guide recovery of the victims remains. Two pigs were deployed, one wrapped in a tarp to reflect the victim’s circumstances and the other uncovered in a time period and flow condition comparable to what was known of the homicide. The results of the transport are reported, along with the successful recovery of the victim’s remains near one of the pig cadavers. Although small in scope and un-replicated, this case study should be a valuable contribution to knowledge of full body human fluvial taphonomy in the future and help inform future search efforts of comparable systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".