Archeologia urbana ad Alghero: dal <i>Castellas</i> al Monastero di Santa Chiara
Bibliographic record
Abstract
The aim of this research is to define, using material heritage, the historic and socio-economic dynamics that in medieval and post-medieval times governed the harbour town of Alghero, located in North-west Sardinia. Founded in the Middle Ages, the town was a stopover of primary importance for traffic in the Mediterranean basin; it has been the focal point of a detailed urban archaeology programme for some twenty years. \n The research concerns a heterogeneous set of findings, both ceramic and numismatic, in the excavations of a part of the old town occupied in the early Middle Ages by the Jewish quarter, which contributed to the busy trade of Alghero. An analysis of the ceramic relics enabled us to define from morphological, typological and functional standpoints the variety of pottery for the table and for transportation used by the community of Alghero in the Jewish quarter and before this existed. \nNumismatic findings enabled new data to be added to what is already known today regarding the circulation of coins in Alghero and North Sardinia. \n The possibility of matching up information on the areas of provenance of the ceramics and coins, important trading markers, led us to reach certain conclusive considerations on the internal organisation of the geopolitical and economic situation of which the town of Alghero was part, comprising Western Europe and the west Mediterranean basin.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".