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Record W4289637821 · doi:10.1371/journal.pone.0270305

Correlative tomography and authentication features of a shrunken head (tsantsa)

2022· article· en· W4289637821 on OpenAlexaff
Lauren September Poeta, María Patricia Ordóñez, Éric Fournier, Andrew J. Nelson

Bibliographic record

VenuePLoS ONE · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicPaleopathology and ancient diseases
Canadian institutionsObject Research Systems (Canada)Western University
Fundersnot available
KeywordsCorrelativeRepatriationAuthentication (law)Computed tomographyRadiologyHistoryMedicineArchaeologyLinguistics

Abstract

fetched live from OpenAlex

Museum personnel and the general public have become quite familiar with the presence of shrunken heads in museum collections, but the procedures to authenticate the history and origin of these unique cultural items are not yet reliable. These shrunken heads, called tsantsas, are meant to be the cultural material remains of ceremonies conducted by the Shuar and Achuar Peoples of South America. This project seeks to integrate the use of micro-computed tomography (micro-CT) scanning with methods used in previous studies (clinical computed tomography (CT) and visual inspections) to examine authentication procedures of shrunken heads (tsantsas) held in contemporary museum collections. We use a correlative tomographic approach using several scans at successively higher resolutions to determine whether a tsantsa was created from human remains, and if so, what key features can best contribute to its authentication. Conclusively, our correlative tomographic approaches provide new insights into the determination process of whether a tsantsa was created from real human remains or not. Also, this study questions whether the previously conceptualized dichotomy of ceremonial or commercial might be better thought of as a continuum of practice. Investigating and redefining the examination and authentication procedures of tsantsas is crucial for future ethical curation, management, and repatriation efforts of this unique cultural material of the Shuar and Achuar Peoples.

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 score0.697
Threshold uncertainty score0.791

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 studies0.0000.000
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 head0.058
GPT teacher head0.228
Teacher spread0.170 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicPaleopathology and ancient diseasesFrench-language works237,207