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Record W4406980482 · doi:10.1016/j.isci.2025.111927

Where Typhoeus lived: 87Sr/86Sr analysis of human remains in the first Greek site in the Western Mediterranean, Pithekoussai, Italy

2025· article· en· W4406980482 on OpenAlexfundno aff
Melania Gigante, Carmen Esposito, Federico Lugli, Alessandra Sperduti, Teresa Cinquantaquattro, Bruno D’Agostino, Alessia Nava, Wolfgang G. Müller, Luca Bondioli

Bibliographic record

VenueiScience · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicPaleopathology and ancient diseases
Canadian institutionsnot available
FundersH2020 Marie Skłodowska-Curie ActionsRoyal Holloway, University of LondonHorizon 2020HORIZON EUROPE Framework ProgrammeUniversità degli Studi di PadovaEuropean Research CouncilQueen's UniversityEuropean Commission
KeywordsMediterranean climateGeographyArchaeology

Abstract

fetched live from OpenAlex

The archaeological heritage of Pithekoussai offers a unique insight into the dynamics of human mobility and biocultural interactions at the dawn of the Magna Graecia during the Iron Age Mediterranean. Pithekoussai was founded by Greeks on the volcanic island of Ischia in southern Italy in the mid-eighth century BC, marking the earliest Greek settlement in the western Mediterranean. The archaeological evidence suggests that Pithekoussai was an emporium where local communities, Greeks, Phoenicians, and people from the mainland lived together and interacted. Despite the challenges posed by the active volcanic burial environment, which affected the preservation of human remains, this study successfully applied strontium isotope analysis ( 87 Sr/ 86 Sr) to n = 71 inhumed and cremated individuals. Integrating biogeochemistry and (bio)archaeology, this research enriches the narrative of human mobility by providing a nuanced reconstruction of the life histories of the individuals who participated in a crucial moment in Mediterranean history that shaped societies at the emergence of Magna Graecia.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.287
Teacher spread0.245 · 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

Citations4
Published2025
Admission routes1
Has abstractyes

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