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Agonal Sequences in a Filmed Suicidal Hanging: Analysis of Respiratory and Movement Responses to Asphyxia by Hanging*

2007· article· en· W2080683009 on OpenAlexaff
Anny Sauvageau, Stéphanie Racette

Bibliographic record

VenueJournal of Forensic Sciences · 2007
Typearticle
Languageen
FieldMedicine
TopicRestraint-Related Deaths
Canadian institutionsConcordia UniversityUniversité du Québec
Fundersnot available
KeywordsDecerebrationAsphyxiaDecorticationMuscle toneMedicineRespiratory systemHyperventilationPoison controlAnesthesiaPsychologyMedical emergencyAnatomySurgeryPhysical medicine and rehabilitationReflex

Abstract

fetched live from OpenAlex

The forensic literature on the pathophysiology of human hanging is still limited. Therefore, forensic pathologists often feel uncomfortable when confronted with related questions. Here presented is the filmed suicidal hanging of a 37-year-old man. This recording allows a unique analysis of agonal movement sequences: loss of consciousness (13 sec), convulsions (15 sec), decortication rigidity (21 sec), decerebration rigidity (46 sec), second decortication rigidity (1 min 11 sec), loss of muscle tone, (1 min 38 sec) and last isolated muscle movement (4 min 10 sec). As for respiratory responses, very deep respiratory attempts started at 20 sec. Respiratory movements progressively decreased and completely stopped at 2 min. Despite the fact that extending the presented data on all cases of hanging asphyxia would be a mistake, this case gives a very interesting insight into movement and respiratory response to asphyxia by hanging.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.034
GPT teacher head0.340
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations36
Published2007
Admission routes1
Has abstractyes

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