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Record W7034204422

Sexsomnia – Excusable or Just Insane?

2015· article· en· W7034204422 on OpenAlexaboutno aff

Bibliographic record

VenueGriffith Research Online (Griffith University, Queensland, Australia) · 2015
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsnot available
Fundersnot available
KeywordsAcquittalAppealVerdictInsanityAutomatism (medicine)Jury
DOInot available

Abstract

fetched live from OpenAlex

In a number of recent cases, people charged with sexual offences have raised sexsomnia as a defence. Sexsomnia is a variant of sleepwalking, and the gist of the defence is that the accused’s conduct was involuntary, carried out while in an automatistic state. The law recognises two types of automatism: sane and insane.The former results in a complete acquittal whereas the latter leads to a special verdict of not guilty on the grounds of insanity or mental illness/impairment/disorder. Judges in Canada, England and Australia have relied on tests such as the internal/external and continuing danger tests to determine whether automatism is caused by a disease of the mind, and therefore insane. However, these tests are unhelpful in sexsomnia cases and the outcomes have been inconsistent. The recent Canadian Court of Appeal case of R v Luedecke provides a useful model for future sexsomnia cases.

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)0.007
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.011
Scholarly communication0.0040.005
Open science0.0010.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.625
GPT teacher head0.482
Teacher spread0.144 · 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 designCase report
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

Citations0
Published2015
Admission routes1
Has abstractyes

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