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Record W7056158186

Echos In The North. Excerpted from The Loons Gift By Victor J Searles

2023· dissertation· en· W7056158186 on OpenAlexaboutno aff

Bibliographic record

VenueRepositorio Institucional de la Universidad de Alicante (Universidad de Alicante) · 2023
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsGuitarPianoTranscription (linguistics)MusicalNatural (archaeology)CraftMusical form
DOInot available

Abstract

fetched live from OpenAlex

I have chosen to transcribe parts of an unpublished original contemporary piano score excerpted from the ballet "The Loon’s Gift" written by Victor John Searles, a gifted British/Canadian musician who was well known locally, but otherwise undiscovered by the international music community. "The Loon's Gift" is one of six ballets he composed in the late twentieth century. I have given the finished transcription a new title "Echos In The North" in reference to the natural habitat of the water bird Loon. This score provided me with the unique opportunity to write the very first classical guitar transcription of the original work. It also created unique challenges that tested my developing musical abilities. Choosing which sections from the original score that would sound and play well on the guitar was only the first step in a process of exploration into both the motivation and structure of the original score. Keeping the fundamental qualities of dramatic atmosphere and emotion evoked through the unique capabilities of the piano while translating them into the equally unique language of the guitar required both respect for the original work and sensitivity to musical possibilities provided by the guitar. My intent in this transcription is to manage this bilingual translation in ways that are both true to the original and authentic to the guitar.

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)0.001
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.007
GPT teacher head0.258
Teacher spread0.251 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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