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Record W3046300429 · doi:10.7202/1070634ar

A Perfect Fifth of Blue and Red: Enlightened Harmonies of the Senses

2020· article· en· W3046300429 on OpenAlexvenueno aff
Edward Halley Barnet

Bibliographic record

VenueJournal of the Canadian Historical Association · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Philosophy and Science
Canadian institutionsnot available
Fundersnot available
KeywordsHarpsichordAppealMusicalPropositionCounterpointPianoClassical musicArtMOZARTAestheticsVisual artsLiteraturePhilosophyArt historyPsychologyEpistemology

Abstract

fetched live from OpenAlex

In this article, I use Louis-Bertrand Castel’s attempt to create a music of colours as a window into 18th-century debates on the inter-relationship between physics, physiology, and sense experience. In part one, I address Castel’s original 1725 proposition to build an “ocular harpsichord,” a musical instrument designed to play colour rather than sound. I argue that Castel’s idea relied in equal measure on contemporary music theory, optics, and neurophysiology. In part two, I examine Castel’s attempts to justify his new music experimentally. Though his purported demonstrations became more eclectic, the core theoretical principles behind his optical music remained the same. In part three, I turn to what should have been the triumph of Castel’s career: his creation of a partially functioning harpsichord in 1755, along with the publication of two proposals for other sensorial musics in 1753 and 1755. The ostensible failure of Castel’s idea points to the limitations — theoretical, experimental, aesthetic — of his original proposal. At the same time, their enduring power to inspire spoke to the appeal of music as an explanatory framework, encompassing both art and science, body and mind.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.171
Teacher spread0.139 · 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 teacher head, 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
Published2020
Admission routes1
Has abstractyes

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