Suicidal Decapitation Using a Tractor Loader: A Case Report and Review of the Literature
Bibliographic record
Abstract
In forensic practice, decapitated bodies are predominantly associated with decapitation by wheels of trains or with postmortem dismemberment following homicide. In the suicidal context, decapitation accounts for less than 1% of total suicide. Apart from decapitation by trains, other encountered methods involve suicidal hanging and vehicle-assisted ligature suicide. Reported here is a unique case of suicidal decapitation in a 45-year-old man using a tractor loader at the foot of a silo, on his farm. The head was recovered in the loader and there were several impact spots from the loader as well as blood on the silo wall. The autopsy revealed a complete decapitation wound with the severance plane located between the third and fourth cervical vertebra. A 1.5 cm wide abrasion on the anterior part of the neck and abrasions under the chin were noted. This very unique case of intentional suicidal decapitation is the first reported case of a planned system intended to create decapitation outside the unique case of homemade guillotine and the more common decapitation by train.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".