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Record W7116778861 · doi:10.1080/00085030.2025.2602964

Determination of vertebrate scavenger guilds in southwestern Ontario

2025· article· en· W7116778861 on OpenAlexafffundvenueabout
Olivia K. Brannagan, Christopher J. Watson, Shari L. Forbes

Bibliographic record

VenueCanadian Society of Forensic Science Journal · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsParks CanadaUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVertebrateScavengerEctothermBiodiversityPopulation

Abstract

fetched live from OpenAlex

When a body is exposed to the natural environment, there are a multitude of taphonomic agents that can affect the remains. One taphonomic agent that has not been extensively studied in Canada is vertebrate scavengers. Although in recent years vertebrate scavenging studies have occurred in several provinces, Canada is a large country with many environmental and climate types. This study aimed to determine the scavenger guild of a rural region of Leamington, in southwestern Ontario. Pig carcasses were surface deposited at a secure location which was accessible to scavengers with placement of two carcasses each in Fall 2023 and Summer 2024, respectively. Scavenging activity was captured using cellular and non-cellular trail cameras. Images were qualitatively analyzed to establish species interaction with the carcasses. It was found that the number of species was limited, but the presence of certain species was prevalent. At all sites, opossums and coyotes were the most frequent scavengers, with coyotes being responsible for the movement and dispersal of the carcasses. The study findings can provide valuable information when searching for human remains in this area or in other areas with similar terrain, climate and species.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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.

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

Citations0
Published2025
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Society of Forensic Science JournalSame topicAquatic Invertebrate Ecology and BehaviorFrench-language works237,207