Intense community dynamics in the pre-Roman frontier site of Fermo (ninth–fifth century BCE, Marche, central Italy) inferred from isotopic data
Bibliographic record
Abstract
Abstract The Early Iron Age in Italy (end of the tenth to the eighth century BCE) was characterized by profound changes which influenced the subsequent political and cultural scenario in the peninsula. At the end of this period people from the eastern Mediterranean (e.g. Phoenicians and Greek people) settled along the Italian, Sardinian and Sicilian coasts. Among local populations, the so-called Villanovan culture group—mainly located on the Tyrrhenian side of central Italy and in the southern Po plain—stood out since the beginning for the extent of their geographical expansion across the peninsula and their leading position in the interaction with diverse groups. The community of Fermo (ninth–fifth century BCE), related to the Villanovan groups but located in the Picene area (Marche), is a model example of these population dynamics. This study integrates archaeological, osteological, carbon (δ13C), nitrogen (δ15N) (n = 25 human) and strontium (87Sr/86Sr) isotope data (n = 54 human, n = 11 baseline samples) to explore human mobility through Fermo funerary contexts. The combination of these different sources enabled us to confirm the presence of non-local individuals and gain insight into community connectivity dynamics in Early Iron Age Italian frontier sites. This research contributes to one of the leading historical questions of Italian development in the first millennium BCE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".