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Record W7018257171

Compositions Inspired by Shotokan Karate Katas

2017· other· en· W7018257171 on OpenAlexaff

Bibliographic record

VenueYorkSpace (York University) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsYork University
Fundersnot available
KeywordsNucleofectionTSG101HyporeflexiaDiafiltrationGestational periodDysgeusiaProteogenomics
DOInot available

Abstract

fetched live from OpenAlex

This compositional thesis consists of six works inspired by the katas or forms of the Shotokan karate style. A kata is a fixed sequence of karate movements with an embedded natural rhythm. The Origins of Shotokan section reviews the history of martial arts in Asia and introduces some of the underlying inspirational elements such as techniques based on animal predatory movements and the katas unique names.
\n The Kata Common Elements section expands on the meaning and structure of a kata. The traditional documentation of the natural rhythm ignores the move to move time interval. This thesis introduces the use of Western music notation to capture the timing relationships and to explain the katas natural rhythm. Four composition sections use a melodic line that is influenced by the physical movement of the karate technique. Picture examples are used to clarify the linkage to the melody. The later sections describe the history of the six inspirational katas. The compositional decisions associated with each is described with respect to their origin, katas name, natural rhythm, orchestration and melodic lines. The musical score accompanies the respective descriptions.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.012

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 head0.016
GPT teacher head0.216
Teacher spread0.200 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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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