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Record W2990271540 · doi:10.5539/res.v11n4p70

A LEOPARD OR A PANTHER? The Pairs of the Stag and the Predator in Vittore Carpaccio's Meditation on the Passion

2019· article· en· W2990271540 on OpenAlexvenueno aff
Atara Moscovich

Bibliographic record

VenueReview of European Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEurasian Exchange Networks
Canadian institutionsnot available
Fundersnot available
KeywordsMeditationPassionPredatorMotif (music)Interpretation (philosophy)PsychologyEcologyEnvironmental ethicsSocial psychologyAestheticsPredationArtPhilosophyTheologyBiologyLinguistics

Abstract

fetched live from OpenAlex

The current paper will suggest an interpretation of two pairs of animals featured in Vittore Carpaccio's Meditation on the Passion, i.e., a stag and a predator of the Felidae family, which in one case devours the stag, and in the other – follows it. The paper will attempt to answer the question why did Carpaccio choose to paint the same motif twice, and why in two differing variations? The aim of this paper is to contribute to the research of the iconography of Job, and to the research on animal symbolism in art, and particularly the ongoing effort to decipher Carpaccio's Meditation on the Passion. Its specific and unique contribution will be to suggest a new interpretation to the peaceful predator, presented on right-hand side in Carpaccio's Meditation, seeing it in a new light – not as a wild animal tamed by a religious transformation, as suggested in previous literature, but rather as an inherently positive one. This reading will be informed by primary sources, which will be connected here with the stag and their predators in Carpaccio's Meditation for the first time.

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 score0.004
Threshold uncertainty score0.011

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 studies0.0010.008
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.086
GPT teacher head0.362
Teacher spread0.276 · 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
Published2019
Admission routes1
Has abstractyes

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