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Record W646175394 · doi:10.33137/rr.v33i4.15983

Leonardo da Vinci and the Art of Sculpture

2011· article· en· W646175394 on OpenAlexvenueno aff
Gary M. Radke, Martin Kemp, Filomena Calabrese

Bibliographic record

VenueRenaissance and Reformation · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicArchitecture and Art History Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSculptureArtVisual artsArt history

Abstract

fetched live from OpenAlex

Leonardo da Vinci (1452--1519) is renowned as a painter, designer, draftsman, architect, engineer, scientist, and theorist. His work as a sculptor is not commonly acknowledged, and many have argued that Leonardo believed that sculpture was an inferior art form (of lesser genius than painting). Challenging and overturning these assumptions, Leonardo da Vinci and the Art of Sculpture looks at the sculptural projects that the artist undertook, as well as the late Renaissance sculptures that were indebted to him. Leonardo consistently drew inspiration from ancient sculpture, admired the work of such contemporary sculptural innovators as Donatello, and even trained under Andrea del Verrocchio, the preeminent bronze sculptor of late 15th-century Florence. Furthermore, Leonardo spent many years of his life working on two larger-than-life-sized horse sculptures--Sforza and Trivulzio--monuments to Francesco Sforza, the Duke of Milan, and to Gian Giacomo Trivulzio, his sucessor. Although neither was completed, the authors argue that these equestrian monuments show how Leonardo was intensely engaged with the design dilemmas of representing a horse rearing on its hind legs. Another highlight of the book is a group of new images of the John the Baptist Preaching to a Levite and a Pharisee, a recently restored large-scale work in the Florentine Baptistery that clearly demonstrates Leonardo's collaboration with Giovanni Rustici.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.012
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.027
GPT teacher head0.194
Teacher spread0.167 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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