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Record W2168084718 · doi:10.1603/me13050

The Role of Spatial Aggregation in Forensic Entomology: Table 1.

2014· article· en· W2168084718 on OpenAlexaff
Justin G. Fiene, Gregory A. Sword, Sherah L. VanLaerhoven, Aaron M. Tarone

Bibliographic record

VenueJournal of Medical Entomology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCarrionForensic entomologyBiologyArthropodReplicateEcologyEntomologyEcological successionLarva

Abstract

fetched live from OpenAlex

A central concept in forensic entomology is that arthropod succession on carrion is predictable and can be used to estimate the postmortem interval (PMI) of human remains. However, most studies have reported significant variation in successional patterns, particularly among replicate carcasses, which has complicated estimates of PMIs. Several forensic entomology researchers have proposed that further integration of ecological and evolutionary theory in forensic entomology could help advance the application of succession data for producing PMI estimates. The purpose of this essay is to draw attention to the role of spatial aggregation of arthropods among carrion resources as a potentially important aspect to consider for understanding and predicting the assembly of arthropods on carrion over time. We review ecological literature related to spatial aggregation of arthropods among patchy and ephemeral resources, such as carrion, and when possible integrate these results with published forensic literature. We show that spatial aggregation of arthropods across resources is commonly reported and has been used to provide fundamental insight for understanding regional and local patterns of arthropod diversity and coexistence. Moreover, two suggestions are made for conducting future research. First, because intraspecific aggregation affects species frequency distributions across carcasses, data from replicate carcasses should not be combined, but rather statistically quantified to generate occurrence probabilities. Second, we identify a need for studies that tease apart the degree to which community assembly on carrion is spatially versus temporally structured, which will aid in developing mechanistic hypotheses on the ecological factors shaping community assembly on carcasses.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.842
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.008
GPT teacher head0.236
Teacher spread0.227 · 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 designOther design
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

Citations26
Published2014
Admission routes1
Has abstractyes

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