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Record W2793171313 · doi:10.48258/arc.v8i4.1509

Il progetto “D12” - Promuovere il rilievo 3D per stimolare la ricerca

2018· article· it· W2793171313 on OpenAlexaff
Federica Guidi, Marinella Marchesi, Giacomo Vianini, Pier Carlo Ricci, Michele Agnoletti, Andrea Rossi

Bibliographic record

VenueAromatic technologies for cultural heritage (mediaGEO) · 2018
Typearticle
Languageit
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsSafe Drinking Water Foundation
Fundersnot available
KeywordsDocumentationArchaeology3d modelArtComputer scienceComputer graphics (images)GeographyArtificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

The Archaeological Museum of Bologna has tested the application of digital technologies on some objects within the project "D12", aimed to connect 3D documentation with polychromy data. An Etruscan stela from Bologna, called "Ducati 12”, gives its name to the project. 3D scanning tests made on some Etruscan artifacts within the project prove that nowadays archaeological and artistic material can be investigated through a low-cost, time-saving and reliable approach. Several 3D virtual data digital technologies were tested and after the postprocessing treatment some real applications on 3D data were realized. Multispectral and chemichal investigations were carried out on the objects. The results achieved allow to undertake an effective research project for the reconstruction of the polychromy in Etruscan age.

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)0.003
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.029
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0290.008

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 head0.025
GPT teacher head0.251
Teacher spread0.225 · 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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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