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Record W4200618652 · doi:10.4000/techne.9189

La campagne de restauration de dix reliefs en stuc italiens dans le cadre du programme ESPRIT : aspects matériels d’une réhabilitation

2021· article· fr· W4200618652 on OpenAlexaff
Alexandra Gérard

Bibliographic record

VenueSpotlight · 2021
Typearticle
Languagefr
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsCentre de Santé et de Services Sociaux de la Montagne
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

En quatre ans, de 2014 à 2018, le programme ESPRIT (Étude des stucs polychromés de la Renaissance italienne) a permis la restauration d’une dizaine de reliefs en stuc italiens de la Renaissance : sept du département des sculptures du musée du Louvre et trois du musée des Beaux-Arts de Strasbourg. Tous restaurés dans les ateliers du Centre de recherche et de restauration des musées de France, ils ont fait l’objet de diverses analyses et du suivi d’un comité de restauration. Ces reliefs forment un corpus homogène et représentatif des différentes problématiques propres à la restauration de ce type d’objet. En l’absence d’archives ou presque, ils ont bénéficié d’une approche méthodologique et déontologique commune impliquant notamment la mise en place systématique d’études préalables avant restauration. Au terme de ces études de cas, on peut distinguer trois niveaux d’intervention de restauration en fonction de l’état de conservation de chaque œuvre, en particulier de sa polychromie.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.219
Teacher spread0.205 · 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.

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
Published2021
Admission routes1
Has abstractyes

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