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Record W2765285437 · doi:10.29173/comp14

Gluten-Free Rome: Celiac disease in the bioarchaeological record

2017· article· en· W2765285437 on OpenAlexaffvenue
Rachel Simpson

Bibliographic record

VenueCOMPASS · 2017
Typearticle
Languageen
FieldMedicine
TopicCeliac Disease Research and Management
Canadian institutionsMacEwan University
Fundersnot available
KeywordsDiseaseDomesticationGlutenHistoryPaleopathologyAgricultureMedicineBiologyArchaeologyPathologyEcology

Abstract

fetched live from OpenAlex

Celiac disease, an autoimmune disorder triggered by consumption of the gluten protein, is theorized to have originated alongside the domestication of wheat during the European Agricultural Revolution, ca. 8 000 BCE (Freeman 2013). Human conditions that primarily affect soft tissue, like celiac disease, do not leave tangible evidence on the skeleton and therefore it is difficult to prove their presence. However, recent analyses have employed a suite of macroscopic, molecular, and chemical techniques to establish that a Roman Imperial (100–300 CE) individual from Cosa, Italy, likely suffered from celiac disease. This paper analyzes the works of these researchers and argues that this case study exemplifies modern bioarchaeology, which frequently requires an arsenal of methods beyond visual observation. Using similar syntheses of techniques bioarchaeologists can possibly identify celiac disease in individuals predating 100 CE, recreating the origins of celiac disease as well as tackling other previously ‘impossible’ research questions in this field.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.011
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
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 head0.054
GPT teacher head0.345
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2017
Admission routes2
Has abstractyes

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