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Record W2907309535

LEAD EXPOSURE IN A MIDDLE CLASS POPULATION OF ANCIENT ROME

2018· report· en· W2907309535 on OpenAlexfundno aff
Jerome O. Nriagu, Mitsuyo Sakamoto

Bibliographic record

VenueDeep Blue (University of Michigan) · 2018
Typereport
Languageen
FieldArts and Humanities
TopicAncient and Medieval Archaeology Studies
Canadian institutionsnot available
FundersDepartment of Anthropology, McMaster UniversitySchool of Public Health, University of MichiganMcMaster University
KeywordsLead (geology)Class (philosophy)PopulationGeographyAncient historyHistoryGeologyComputer scienceMedicineEnvironmental healthArtificial intelligencePaleontology
DOInot available

Abstract

fetched live from OpenAlex

The cemetery population of Isola Sacra dates to the 2nd and 3rd centuries AD and consisted of middle class traders and craftsmen as suggested by tomb inscriptions. We present data to show that most of the skeletal remains (humans as well as domestic animals) at the site have become diagenetically contaminated with lead. Analysis of 22 bones from protected monumental tombs, believed to be free of post-mortem changes, shows average lead concentration of 10 μg/g, with the range being 0.87-36 μg/g. The observed bone lead levels are comparable to values that have been reported for many modern urban populations. Calculated average blood lead level was 10 μg/dL (range, 0.89-36 μg/dL) and suggest that exposure to lead was not just restricted to the aristocracy but was pervasive among all social classes of the Roman population. The health risk of the suspected lead exposure dose would have been marginal for the adult population but likely inimical to children. The isotopic composition of the bone lead suggests that the cemetery population obtained their lead from multiple ancient sources. The aim of releasing this report is to encourage further debate and research on the role of lead poisoning in the decline of the ancient Roman Empire

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.051
GPT teacher head0.223
Teacher spread0.172 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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