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Record W4408694797 · doi:10.5744/fa.2024.0002

From a Small Plot in Knoxville to a Worldwide Footprint

2025· article· en· W4408694797 on OpenAlexaff
Melissa Connor, William Belcher, Gretchen R. Dabbs, Anthony B. Falsetti, Shari L. Forbes, Timothy P. Gocha, Sheree Hughes‐Stamm, Ginesse Listi, Sophia R. Mavroudas, Austin Polonitza, Sophia Reck, Dawnie Wolfe Steadman, Jodie Ward, Daniel J. Wescott, An‐Di Yim, Katie Zejdlik

Bibliographic record

VenueForensic Anthropology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPlot (graphics)FootprintEnvironmental scienceGeographyStatisticsMathematicsArchaeology

Abstract

fetched live from OpenAlex

The first outdoor human decomposition research facility was established by Dr. William Bass in 1980 at the University of Tennessee in Knoxville. Initial research at the Anthropology Research Facility (ARF) examined some of the large-scale environmental factors that contribute to decomposition and time since death estimates. As taphonomic research grew into a holistic and interdisciplinary field, the importance of macro-and microenvironmental factors became clear, and additional facilities opened in different areas of the globe. Research conducted at outdoor decomposition facilities now investigates complex relationships between the decomposing body and its environment in diverse landscapes across the world. These facilities play an important role in forensic science by providing real-world laboratory environments, research material, opportunities for research, and documented modern skeletal collections. In addition, they provide opportunities for training both professionals and students in many fields that require human remains, including human remains recovery, death investigation, and cadaver dog training. In the United States today, the resulting ethically donated human skeletal collections have increasing importance in understanding the changes in modern human bodies. This article examines the growth and function of what have been colloquially referred to as “body farms” over the past four decades.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.018
GPT teacher head0.266
Teacher spread0.248 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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