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Record W4380048010 · doi:10.32473/jvfs.2.1.130161

Forensic evaluation of a dog with an embedded chain collar and corresponding wound age estimation

2023· article· en· W4380048010 on OpenAlexaffabout
Danielle Renée Godard, Sean P. McDonough, Shelagh Copeland

Bibliographic record

VenueJournal of Veterinary Forensic Sciences · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsShared HealthUniversity of SaskatchewanAgriculture Food and Rural Development
Fundersnot available
KeywordsGranulation tissueCollarMedicineSurgeryWound healing

Abstract

fetched live from OpenAlex

The body of a young intact male dog was presented with an embedded chain collar around his neck as possible evidence in proceedings under the Criminal Code of Canada. A photographic record was made for court purposes. The circumference of the collar versus the adjacent unaffected neck was measured, showing the collar to be 15% shorter than was necessary to be compatible with non-injury to the dog while alive. Granulation tissue and fibrosis were grossly and histologically evaluated to help estimate the age of the wound. The granulation tissue at its deepest point was 2.0 cm. Considering granulation tissue begins formation 3–5 days post-injury and forms at a rate of 0.4–1.0 mm per day, the initial age of the wound was estimated at 23–55 days; however, given the re-epithelialization and fibrous strength of the affected tissue as well as the presence of haired skin around the links, the time estimate was determined to be more likely in the order of 4–6 months. Findings were later used in court as evidence in the charge of unnecessary pain, suffering and injury to an animal under Section 445.1(1)(a) of the Criminal Code. Testimony at the trial supported the estimated age of the wound. The owner was found guilty, fined Can$1000, placed on probation for two years, and prohibited for life from owning animals.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.087
GPT teacher head0.363
Teacher spread0.277 · 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 designBench or experimental
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

Citations1
Published2023
Admission routes2
Has abstractyes

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