The taphonomic impact of scavenger guilds in southern Quebec during summer and fall in two distinct habitats
Bibliographic record
Abstract
Decomposition of human remains is a complex process impacted by many intrinsic and extrinsic factors. A less-studied extrinsic factor in forensic taphonomy are the scavengers that consume soft and hard tissue. Scavengers physically degrade and remove soft tissue, disperse, and destroy skeletal elements, which can make locating remains challenging. While invertebrate activity has been largely investigated, there is limited quantitative data available on vertebrate activity, particularly in Canada. This study aimed to determine which species (vertebrate and invertebrate) belong to the scavenger guilds in southern Quebec, and their potential taphonomic impact on the decomposition process. Two independent trials were conducted in 2020 using pig carcasses: one during summer in a forest habitat and one during fall in a grassland habitat. Each carcass was placed a minimum 100 m apart in semi-rural land. Vertebrate scavenger activity was recorded by continuous surveillance using trail cameras. Carcasses were also regularly visited to monitor the decomposition process and the activity of invertebrate scavengers. Overall, the vertebrate scavenger guilds included a narrow range of corvids, turkey vultures, coyotes, and skunks. The intensity of vertebrate scavengers was greater in the grassland habitat (fall), while the intensity of invertebrate scavengers was greater in the forest habitat (summer). With the exception of invertebrate scavengers, very few species visited during the fresh stage of decomposition, and the probability of body displacement increased as decomposition progressed. These results identify which scavengers have the greatest taphonomic impact and highlight the importance of incorporating scavenger impact when searching for human remains.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".