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Record W2757804460 · doi:10.3968/9725

On the Analysis of the Style and Feature of Wang Zhixin’s Vocal Music Composition

2017· article· en· W2757804460 on OpenAlexvenueno aff
Hong Lin

Bibliographic record

VenueCross-cultural communication · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSingingComposition (language)Style (visual arts)Vocal musicOperaArtFeature (linguistics)MusicalSpeech recognitionMusical compositionVariety (cybernetics)LiteratureLinguisticsMusicVisual artsComputer scienceAcousticsMusic educationPhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

Wang Zhixin is a famous vocal music composer and conductor in China. He has created hundreds of renowned vocal composition in his past forty years of musical art career, for instance, Lan Huahua (The Flower of Orchid), Meng Jiangnv (The Legend of A Loyal Widow), The Spring of China, Mei Huayin (Ode to the Plum Blossom). All of these mentioned above are his most representative works. He absorbs not only the singing methods from the folk tunes and traditional Chinese opera, but also the composition skills on modern vocal music. His composition, thus, is full of multi-nationality, particularity of times and multi-variety. This paper will elaborate on the above three aspects to analyze the Style and Feature of Wang Zhixin’s Vocal Music Composition.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.999

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 studies0.0020.002
Scholarly communication0.0010.000
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 head0.102
GPT teacher head0.305
Teacher spread0.202 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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