A Report of Decomposition Rates of a Special Burial Type in Edmonton, Alberta from an Experimental Field Study
Bibliographic record
Abstract
Regional studies that examine decomposition rates of certain faunal remains can help to determine time since death. Forensic anthropologists have long used qualitative decomposition data, but linking these to more quantitative data could improve time since death estimations. Experiments were developed in which domestic pigs (Sus scrofa) were buried with varying characteristics then excavated and observed over a period of 15 months in Edmonton, Alberta. Data recorded after two weeks, five weeks, three months, one year, and 15 months were correlated with stages of decomposition as well as time since death, climate data, grave type, clothing, burial depth, and other factors. Results from these experiments provide useful regional information about stages of decomposition in a burial context. Pigs buried in June were skeletonized by approximately three to five weeks, while those buried in May were skeletonized between five weeks and three months. Climate data, insects, and grave type contributed the most to advanced decomposition, mainly in the form of mummification, and skeletonization.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".