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Testing Different Search Methods for Recovering Scattered and Scavenged Remains

2008· article· en· W2035829056 on OpenAlexafffundvenue
Sherah L. VanLaerhoven, Carolann Hughes

Bibliographic record

VenueCanadian Society of Forensic Science Journal · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsUniversity of Windsor
FundersUniversity of Windsor
KeywordsHabitatDeciduousEcologyBiologyVertebrateScavengingAbundance (ecology)

Abstract

fetched live from OpenAlex

Vertebrate scavengers are primary mechanisms for scatter and disarticulation of human remains in rural habitats. Because recovery of the body can be hampered by the degree of scatter due to scavengers, the methods used to search for body parts will influence how much is found and the length of time taken to recover the body. We compared the frequency of scavenging by vertebrates in two different habitats, a deciduous forest and a tall grass meadow, and measured the time taken to search for scattered remains within a designated search area using four methods. Freshly killed 23 kg pigs were placed in either a forest or tall grass meadow habitat, and scavenging by vertebrates was observed over a 5–6 day period. Subsequently, the link, line, zone, and spiral methods were used to search for remains within a 21 m2 search area. Three of 5 pigs in the forest and 4 of 5 pigs in the meadow habitat were scavenged by a variety of vertebrates. Mean time to search the designated area around each pig differed between the forest and the meadow, but not by search method. Mobility within each habitat likely explains the difference in search times, and also accounts for some of the variability between search methods.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
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
Bibliometrics0.0000.000
Science and technology studies0.0020.002
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 head0.082
GPT teacher head0.307
Teacher spread0.225 · 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

Citations13
Published2008
Admission routes3
Has abstractyes

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