Estimation of time since death using a body cooling model of pigs: A pilot study
Bibliographic record
Abstract
The aim of this study was to test the effects of Korean floor-heating system on heat loss using adult pig models, and to create a novel formula for estimating time since death during the early stages of decomposition.Three electric mattress pads were placed on the ground to maintain a constant temperature of the substrate like the ondol heating system.Four temperature measuring probes were placed in each pig: inside the rectum, on the body surface, between the body and the surface of mattress pad and on the mattress pad.The probes were connected to a temperature data logger system.Temperature was recorded every minute and statistical analysis was performed using the SAS (version 9.3) program.Spearman's Rank Correlation results demonstrated the rectal temperature, and the temperature between the body and the surface of pad were s t r o n g l y c o r r e l a t e d w i t h postmortem cooling of the body, rather than ambient temperature.The rate of cooling of the body is represented by a cube function of time rather than an exponential or bi-exponential function.This research indicates that postmortem cooling of the body is more influenced by ground surface temperature than by ambient (environment) temperature, and the rectal temperature fluctuated with the ambient temperature.Additionally, the study showed that pigs can be good animal models that can substitute human cadaver to study the process of decomposition.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".