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Record W4403641147 · doi:10.1371/journal.pone.0299788

Where did the herds go? Combining zooarchaeological and isotopic data to examine animal management in ancient Thessaly (Greece)

2024· article· en· W4403641147 on OpenAlexaff
Dimitris Filioglou, Sílvia Valenzuela, William P. Patterson, Leopoldo D. Pena, Samantha Presslee, Sandra Timsic, W. Prummel, Canan Çakırlar

Bibliographic record

VenuePLoS ONE · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsUniversity of Saskatchewan
FundersNational Institute on AgingAlbert-Ludwigs-Universität FreiburgConsejo Superior de Investigaciones CientíficasYorkshire ForwardUniversiteit van AmsterdamUniversity of ThessalyRijksuniversiteit Groningen
KeywordsAnimal husbandryLivestockScale (ratio)GeographyHerdEcologyArchaeologyBiologyAgricultureForestryCartography

Abstract

fetched live from OpenAlex

Historians and archaeologists have been debating the scale of animal husbandry in ancient Greece for decades. This study contributes to the debate by examining Classical and Hellenistic faunal assemblages from Magoula Plataniotki, New Halos, and Pherae through non-destructive zooarchaeological methods and a multi-isotopic (87Sr/86Sr, δ13C, and δ18O) approach. Zooarchaeological data suggest that small-scale sedentary animal husbandry focused on caprine production in Magoula Plataniotiki and New Halos, and small-scale and semi-specialised animal husbandry was practised in Pherae. Isotopic data show both sedentary and mobile management of livestock in all sites, indicating different levels of production intensity and variety of goals. Based on our results, we propose an economic model whereby semi-specialised and small-scale animal husbandry co-existed, confirming mixed husbandry models for ancient Greece.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.082
GPT teacher head0.237
Teacher spread0.155 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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