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Record W3112355943 · doi:10.37558/gec.v18i1.848

Overpaints and inpainting on the “Black flag” by Ljubo Babić

2020· article· en· W3112355943 on OpenAlexaboutno aff
Maja Sucevic Miklin

Bibliographic record

VenueGe-conservacion · 2020
Typearticle
Languageen
FieldNeuroscience
TopicAesthetic Perception and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsInpaintingPaintingDirtOil paintingArtVisual artsProcess (computing)Flag (linear algebra)Computer scienceArtificial intelligenceImage (mathematics)CartographyMathematicsGeography

Abstract

fetched live from OpenAlex

This paper will present the restoration carried out at the end of 2017 on an oil painting called the “Black flag”, by Ljubo Babić, that stands today as one of the five more important paintings in Croatian modern art history. The focus will be on previous interventions – retouches and overpaintings – that were found on such an important painting, as well as the complex process of inpainting.
 After a partial removal of the previous interventions, some particles of dirt were still left embedded in the texture. This condition and the artist's paint effects determined the inpainting process. A mimetic inpainting method was chosen, consisting into a two stages process, intermediated with a varnish application: gouache colours to reconstruct the image and pigments mixed with Canada balsam to finish the process. This method resulted in a good reintegration of the retouch and in the overall appearance of the painting.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.049
GPT teacher head0.240
Teacher spread0.191 · 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 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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