Evidence map›Paper›PMID 37467179›Full record

ArticlePloS one2023

Machine learning-based Sr isoscape of southern Sardinia: A tool for bio-geographic studies at the Phoenician-Punic site of Nora.

Melania Gigante, Alessandro Mazzariol, Jacopo Bonetto, Elena Armaroli, Anna Cipriani, Federico Lugli

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
9.7field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Where Typhoeus lived:iScience · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Melania GiganteDepartment of Cultural Heritage, University of Padua, Padua, Italy.ORCID 0000-0003-4028-4012
Alessandro MazzariolDepartment of Cultural Heritage, University of Padua, Padua, Italy.ORCID 0000-0001-6675-5797
Jacopo BonettoDepartment of Cultural Heritage, University of Padua, Padua, Italy.ORCID 0000-0001-6015-9898
Elena ArmaroliDepartment of Chemical and Geological Science, University of Modena & Reggio Emilia, Modena, Italy.ORCID 0009-0004-6727-7730
Anna CiprianiDepartment of Chemical and Geological Science, University of Modena & Reggio Emilia, Modena, Italy.ORCID 0000-0001-8457-0147
Federico LugliDepartment of Chemical and Geological Science, University of Modena & Reggio Emilia, Modena, Italy.ORCID 0000-0002-5642-2216
University of Modena and Reggio Emilia · ITUniversity of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since prehistoric times, the island of Sardinia-in the western Mediterranean-has played a leading role in the dynamics of human population and mobility, in the circulation of raw materials and artefacts, idioms and customs, of technologies and ideas that have enriched the biological, linguistic and cultural heritage of local groups. For the Phoenician and Punic periods (from the 9th to the 3rd centuries BCE), the ancient site of Nora-in southern Sardinia-represents an emblematic case in the study of migratory phenomena that occurred on the Island from the Iron Age until the Roman conquest. Despite the importance of exploring (and characterising) such movements from a wider bio-cultural perspective, the application of bio-geochemical tools for geographical provenance to the ancient skeletal populations of Sardinia is yet scarce. The present work is the first step towards filling this gap with the development of the first isoscape of southern Sardinia using new bioavailable Sr isotope data and a machine-learning approach. From a geolithological point of view, Sardinia is rather heterogeneous and requires detailed studies to correctly assess the distribution of the isotopic signature of bioavailable Sr. The random forest model employed here to construct the Sr isoscape uses several external environmental and geological variables. The most important predictors are related to age and bedrock type, with additional input from local soil properties. A 10-fold cross-validation gives a mean square error of 0.0008 and an R-squared of 0.81, so the model correctly predicts the 87Sr/86Sr ratio of unknown areas. By using a Bayesian provenance assignment workflow, we tested the isoscape here produced to determine the geographic origin and the mobility of archaeological and modern fauna collected from the Phoenician-Punic site of Nora and the surrounding Pula Plain. Our results indicate that archaeological sheep and goats (87Sr/86Sr < 0.7090) are compatible with areas close to Nora and Pula Plain, in agreement with archaeological evidence of pastoralism in those areas. Modern wild and domesticated fauna (87Sr/86Sr > 0.7090) show compatibility with several natural and anthropogenic locations in southern Sardinia, as expected based on modern species distribution data. Finally, we discuss the large Sr isotopic variability of the Nora baseline, where human mobility studies of human cremated and inhumed individuals are currently underway.

Indexed as

Machine LearningStrontium IsotopesAnimalsBayes TheoremHumansItalySheepStrontium-86Strontium-87Strontium Isotopes

Identifiers

PMID37467179
PMCPMC10355458
OpenAlexW4384818916

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.