Fall Decay Deceleration in Northern Latitudes: Merely a Matter of Cold?
Bibliographic record
Abstract
The decomposition of cadavers and large vertebrate carcasses is the result of complex processes primarily influenced by ambient temperatures. Thus, low temperatures can alter decomposition by curtailing tissue autolysis and bacterial decomposition, and by limiting insect activity contributing to necromass removal. In this study, we tested whether carcass decomposition rate is modulated not only directly by temperature and insect occurrence, but also indirectly by the mediation of interactions among insects by ambient temperature. To test this, a comparative analysis of the decomposition of domestic pig carcasses in summer and fall was conducted in Atlantic Canada. The results indicated that carcass decomposition standardized to account for seasonal differences was significantly decelerated in the fall as opposed to the summer during the later decomposition stages and was sometimes incomplete. Moreover, the arrival, presence, and departure of insects from carcasses during ecological succession differed between summer and fall. Necrodes surinamensis (Fabricius) (Coleoptera: Silphidae) and Creophilus maxillosus (Linnaeus) (Coleoptera: Staphylinidae) maintained higher abundances late during succession in the fall than in the summer and their abundance was related to a decline in decomposition rates, probably because these species feed on dipteran larvae promoting necromass removal. These results demonstrate the variability in response to environmental parameters of insects of forensic importance and support the idea that slowed decomposition in the fall may be exacerbated by changes in interspecific interactions among insects. Furthermore, these results suggest that successional studies of insects carried out in the summer have little forensic utility for cadavers found in cold weather conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".