Three Nonlethal Ligature Strangulations Filmed by an Autoerotic Practitioner
Bibliographic record
Abstract
Despite great advances in forensic sciences in the last decades, our knowledge of the pathophysiology of ligature strangulation is still largely based on old writings from the 19th and beginning of the 20th century. The study of filmed hangings by the Working Group on Human Asphyxia has contributed to a better understanding of the agonal responses to strangulation by hanging, and judo-related studies have given some insight into the pathophysiology of manual strangulation, but the pathophysiology of ligature strangulation has remained largely unexplored so far. Three nonlethal strangulations filmed by an autoerotic practitioner are here presented. In these 3 ligature strangulations, the 35-year-old man is sitting on a chair. A pair of pajama pants is rolled once around his neck, with the extremities of the pants falling down on each side of his chest. The man is pulling the extremities of the pants with both hands to apply compression on his neck. After losing consciousness, he ceases to pull on the ligature, and the pants slowly loosen around the neck. A few seconds later, he regains consciousness and gets up from the chair. In the 3 nonlethal ligature strangulations presented in this study, the loss of consciousness occurred in 11 seconds. The loss of consciousness was closely followed by the onset of convulsions (7-11 seconds). These results are compared with the early agonal responses documented in filmed hangings and judo studies.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".