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Record W1012708311 · doi:10.5206/notabene.v8i1.6599

Harmonic Language in The Legend of Zelda: Ocarina of Time

2015· article· en· W1012708311 on OpenAlexaffvenue
Nicholas C Gervais

Bibliographic record

VenueNota bene · 2015
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsTeleportationLegendSubdominantVariety (cybernetics)Chord (peer-to-peer)Computer scienceTonic (physiology)Context (archaeology)HarmonicTheoretical physicsMathematical economicsLinguisticsPhysicsMathematicsArtificial intelligenceHistoryAcousticsQuantum mechanicsQuantum entanglementPsychologyArtLiteraturePhilosophy

Abstract

fetched live from OpenAlex

This paper examines the work of Koji Kondo in the 1998 video game The Legend of Zelda: Ocarina of Time. Using a variety of techniques of harmonic analysis, the paper examines the commonalities between teleportation pieces and presents a model to describe their organization. Concepts are drawn from the work of three authors for the harmonic analysis. William Caplin’s substitutions; Daniel Harrison’s fundamental bases; and, Dmitri Tymoczko’s parsimonious voice leading form the basis of the model for categorizing the teleportation pieces. In general, these pieces begin with some form of prolongation (often tonic); proceed to a subdominant function; employ a chromatically altered chord in a quasi-dominant function; and, end with a weakened cadence in the major tonic key. By examining the elements of this model in each piece, this paper explains how the teleportation pieces use unusual harmonic language and progressions while maintaining a coherent identity in the context of the game’s score.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.121

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.029
GPT teacher head0.253
Teacher spread0.224 · 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 designObservational
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
Published2015
Admission routes2
Has abstractyes

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