Developing a new scoring method to evaluate human decomposition in a humid, continental (Dfb) climate in Quebec
Bibliographic record
Abstract
The published literature shows a lack of methods to evaluate the patterns and extent of decomposition of human remains and to estimate the post-mortem interval (PMI) in humid, continental (Dfb) climates such as Quebec. The aim of this study was to address this gap in the current knowledge base by providing the first observations from human corpses studied under controlled conditions in Quebec. A 12-month study was conducted at the site for Research in Experimental and Social Thanatology; the first human taphonomy facility in Canada. Six human donors with known time of death were deposited across spring (n = 1), summer (n = 3), and autumn (n = 2) 2021. The lack of suitability of the total body score method to evaluate the extent of decomposition at the facility prompted the development of a new scoring system based on the macromorphoscopic changes observed. The scoring system was applied to the donors to evaluate decomposition throughout seasons. All donors followed comparable decomposition trajectories, regardless of the season of deposition. Eighty-five percent of taphonomic patterns appeared in the first 25 experimental days or 5000 Kelvin accumulated degree days (350 ADD). Extensive desiccation of tissues was observed at a median of 21 experimental days across donors, resulting in a plateau within decomposition with no extensive skeletonization. To the authors' knowledge, this is the first published report of experimentally observed desiccation in such a form in a Dfb climate. This study provides new data on the types of decomposition patterns to expect in forensic investigations in southern Quebec and comparable climates.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".