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Record W4211011170 · doi:10.1016/j.jasrep.2022.103349

Using parasite analysis to identify ancient chamber pots: An example of the fifth century CE from Gerace, Sicily, Italy

2022· article· en· W4211011170 on OpenAlexafffund
Sophie Rabinow, Tianyi Wang, Roger Wilson, Piers D. Mitchell

Bibliographic record

VenueJournal of Archaeological Science Reports · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicPaleopathology and ancient diseases
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaRegione Siciliana
KeywordsIntestinal parasiteParasite hostingCeramicArchaeologyPotteryTrichuris trichiuraBiologyNematodeHelminthsZoologyGeographyEcologyMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Chamber pots are perhaps one of the more challenging ceramic forms to identify with certainty in Roman pottery studies, despite the availability of detailed ceramic typologies. Here, we describe the analysis of mineralized concretions taken from a Sicilian ceramic vessel of the fifth-century CE, and propose paleoparasitology, the identification of intestinal parasites, as a helpful method for contributing to the detection of chamber pots. Microscope analysis of the mineralized concretions revealed the presence of eggs of the intestinal nematode Trichuris trichiura (whipworm), confirming that the vessel originally contained faeces. This is the first time that parasite eggs have been identified from concretions inside a Roman ceramic vessel. Systematic parasitological investigation of calcified deposits from ceramic vessels may therefore help to establish function. In addition, the identification of intestinal parasite eggs has the potential to advance our understanding of the sanitation, diet, and intestinal health of populations who used these chamber pots.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.092
GPT teacher head0.332
Teacher spread0.240 · 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

Citations6
Published2022
Admission routes2
Has abstractyes

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