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Record W3093698917 · doi:10.1002/oa.2930

Interpreting mortuary treatment from histological bone diagenesis: A case study from Neolithic Çatalhöyük

2020· article· en· W3093698917 on OpenAlexaff
Haley P. Goren, Sabrina C. Agarwal, Patrick Beauchesne

Bibliographic record

VenueInternational Journal of Osteoarchaeology · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsTaphonomyHistologyPaleopathologyDiagenesisDifferential diagnosisPathologyArchaeologyBiologyMedicineGeographyPaleontology

Abstract

fetched live from OpenAlex

Abstract This study examines the evidence for differential mortuary practices at the Neolithic site of Çatalhöyük, in Anatolia, Turkey, using the histological examination of bacterial microbioerosion in archaeological human bone. In order to analyse bacterial microbioerosion, thin sections were prepared from the midshaft of thoracic ribs 6–8, of n = 162 individuals (adults and juveniles) and analysed using qualitative analysis of microscopic focal destructive changes with polarized light microscopy. The extent of destructive change was assessed, and the degree of preservation was examined using the Oxford Histological Index. Individual, in situ interment was assessed using burial and skeletal data. Results show no differences in histological bacterial microbioerosion between male and female burials, but histological preservation was seen to differ between juveniles and adults, findings that are interpreted as the result of differential mortuary practices at the time of death. The challenges and potential of examining recurring taphonomic signatures in bone histology and their relationship to differential burial practices are discussed.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.007
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 head0.068
GPT teacher head0.298
Teacher spread0.230 · 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 designQualitative
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

Citations9
Published2020
Admission routes1
Has abstractyes

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