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Record W4405402840

A Preliminary Analysis of Goju-ryu Kata Structure

2012· article· en· W4405402840 on OpenAlexaff
Fernando Portela Câmara, Mario Mckenna

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMartial Arts: Techniques, Psychology, and Education
Canadian institutionsProvincial Health Services Authority
Fundersnot available
KeywordsComputer science
DOInot available

Abstract

fetched live from OpenAlex

Miyagi Chojun (1888-1953) was the founder of Goju-ryu; a karate-do style that purportedly had ties to a Chinese boxing school established on Okinawa in 1828 and was based on the teachings of his primary instructor Higaonna Kanryo (1850-1915). Yet, the continuity of modern Goju-ryu with respect to its katas (forms) and these historical sources has never been established. Therefore, we employed a statistical technique to examine the relationship between the classical katas of modern Goju-ryu. It was reasoned that there would be continuity across all katas of modern Goju-ryu if they indeed came from a similar source. The results were insightful and suggest the possible origins of Goju-ryu katas.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.302
GPT teacher head0.623
Teacher spread0.321 · 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 designQualitative
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
Published2012
Admission routes1
Has abstractyes

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