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Record W2121050513 · doi:10.1017/s0261127912000022

MUSIC, PESTILENCE AND TWO SETTINGS OF <i>O BEATE SEBASTIANE</i>

2012· article· en· W2121050513 on OpenAlexaff
Remi Chiu

Bibliographic record

VenueEarly Music History · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYersinia bacterium, plague, ectoparasites research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPlague (disease)The RenaissanceSAINTArtPatron saintReading (process)Art historyHumanitiesVisual artsHistoryAncient historyLawPolitical science

Abstract

fetched live from OpenAlex

This essay examines the role of music in the late-medieval and Renaissance response to plague. According to doctors, the mere thought of plague could bring on the disease; they therefore prescribed joyful music to distract the mind from insidious imaginings and to counteract the harmful effects of fear. The prescription for music, however, was not unequivocal. Some spiritual authorities looked suspiciously upon music's role as anti-pestilential remedy. These competing discourses inform a reading of Johannes Martini's and Gaspar van Weerbeke's settings of O beate Sebastiane, motets that petition St Sebastian, the premier plague saint of the Renaissance, for divine intervention against pestilence.

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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

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 studies0.0060.021
Scholarly communication0.0050.002
Open science0.0000.003
Research integrity0.0020.003
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 head0.018
GPT teacher head0.238
Teacher spread0.220 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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