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Record W4387786405 · doi:10.26658/jmr.1377336

Villa Gallo Romaine de Séviac - France Approches innovatives visant à la valorisation, à la conservation et à la restauration de pavements de mosaïque antiques exposés en plein air

2023· article· en· W4387786405 on OpenAlexaboutno aff
Paola PERPIGNANI, P. Racagni

Bibliographic record

VenueJournal of Mosaic Research · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicAncient Mediterranean Archaeology and History
Canadian institutionsnot available
Fundersnot available
KeywordsPortugueseArchaeologyMosaicPolychromeArtResidenceHumanitiesHistorySociology

Abstract

fetched live from OpenAlex

The Gallo-roman villa of Séviac, located in the Municipality of Montréal du Gers in France, was accidentally discovered at the end of the 19th century. The archaeological investigations identified the end of the 4th and the beginning of the 5th century as the period of its greatest splendour. It was a large rural residence that certainly belonged to a high-ranking aristocrat, covering a total area of about 25,000 sqm. In ancient times, it is believed to have mosaic floors with a total area of approximately 1,500 sqm. Currently, the site boasts about 400 sqm of beautiful polychrome mosaics of undoubted technical and stylistic quality. Recently, thanks to the interest of the local authorities, it was decided to invest in the territory through a series of programs aimed at protecting and enhancing the historical, artistic and archaeological heritage of the territory. Through a public competition, a team headed by the Portuguese architect João Luís Carrilho da Graça was selected, as it possessed the specific skills in the required fields. A new fully functional and innovative system of coverage of the entire site was designed and built. After a very complex preliminary diagnostic work, the team, in cooperation with the restoration laboratory of RavennAntica Foundation, designed and then directed the restoration of the entirety of the mosaic floors.

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)0.011
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.065
GPT teacher head0.370
Teacher spread0.306 · 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 designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

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