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Psychological Autopsy in the Investigation of Serial Neonaticides

2011· article· en· W2116929601 on OpenAlexaff
Steve Burton, J. Thomas Dalby

Bibliographic record

VenueJournal of Forensic Sciences · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicHomicide, Infanticide, and Child Abuse
Canadian institutionsUniversity of CalgaryCalgary Laboratory Services
Fundersnot available
KeywordsAutopsyInjury preventionSuicide preventionPoison controlMedicineCrime sceneCause of deathPsychiatryPsychologyMedical emergencyDemographyPediatricsCriminologyPathologySociologyDisease

Abstract

fetched live from OpenAlex

While the use of psychological autopsies has at least a 50-year history in the investigation of equivocal deaths and suicides, we report a case where, after the discovery of a woman who died of natural causes, a subsequent search of her home found three deceased newborn infants. The infants were born on three separate occasions; the most recent was delivered approximately 2 weeks before the death of the mother. Using her own diaries and interviews with family and friends along with the physical autopsy and scene investigation data, we built a psychological autopsy that addressed the mother's mental state over the period of time when the infants' deaths took place. While the use of the psychological autopsy was not employed to distinguish the manner of death of the mother, it did provide explanatory power over circumstances of the crime scene and the behavioral disturbance of the mother.

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)0.003
metaresearch head score (Gemma)0.010
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.095
GPT teacher head0.341
Teacher spread0.245 · 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

Citations10
Published2011
Admission routes1
Has abstractyes

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