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Record W2043232290 · doi:10.1111/1556-4029.12684

Specific Patterns of Canine Scavenging in Indoor Settings

2015· article· en· W2043232290 on OpenAlexaff
Thomas Colard, Yann Delannoy, Stephan Naji, Didier Gosset, Kristen M. Hartnett, Anne Bécart

Bibliographic record

VenueJournal of Forensic Sciences · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsScavengingTrunkMedicineTaphonomyHead and neckNoseSurgeryBiologyEcology

Abstract

fetched live from OpenAlex

Postmortem animal mutilations due to domestic dogs in isolated domestic deaths are taphonomic modifications regularly observed by forensic pathologists. They are rarely described in the literature; however, even though they present specific patterns. Through 41 cases, 10 at the forensic institute in Lille (France) and 31 at the New York City Office of Chief Medical Examiner (USA), plus 22 cases from the literature, specific locations and patterns of postmortem scavenging lesions are proposed. These lesions are mainly distributed in three locations: the face, especially the nose and the mouth (73.1%), the neck (43.1%), and the arm (shoulder/upper limb [29.2%], hand [26.8%]). We discuss the time span between death and scavenging, the consequences on identification, and comparison with outdoor settings. Outdoor scavenging lesions are mainly located on the trunk and limbs usually sparing the head, which strongly differs from indoor distribution and imply different animal motivations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.222
Threshold uncertainty score0.208

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.272
Teacher spread0.237 · 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 teacher head, 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

Citations31
Published2015
Admission routes1
Has abstractyes

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