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Record W4313497295 · doi:10.21747/2182-1097/14a11

Imagens de Santa Cecília na pintura portuguesa dos séculos XVII e XVIII: devoção, usos e funções, fontes e modelos

2022· article· en· W4313497295 on OpenAlexfundno aff
Sónia Duarte

Bibliographic record

VenueCEM · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Art and Architecture Studies
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaFederation for the Humanities and Social Sciences
KeywordsIconographyArtPortugueseRepresentation (politics)PaintingHumanitiesMusicalArt historyCartographyVisual artsGeographyPhilosophyPolitical science

Abstract

fetched live from OpenAlex

The survey of musical iconography in Portuguese paintings that we have been carrying out in recent years has revealed a very considerable number of specimens with the representation of Santa Cecilia, especially in the north and center of the country. Patroness of music according to a debatable biographical account that indicates the virgin heard during her wedding the sound of divine music, Santa Cecilia appears to us represented in hagiological strategically placed on the ceiling of coenobias, churches, public and private chapels. Starting from the organisation of the Cecilian image in seven predominant typologies, we will list aspects related to her devotion, sources and models used by painters in representations, as well as the uses and functions of the Cecilian image in Portugal. This first survey and study of the image of Santa Cecília in Portugal is naturally incomplete.

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 score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.005
Scholarly communication0.0040.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.022
GPT teacher head0.203
Teacher spread0.182 · 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
Published2022
Admission routes1
Has abstractyes

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