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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I have chosen to transcribe parts of an unpublished original contemporary piano score excerpted from the ballet "The Loon’s Gift" written by Victor John Searles, a gifted British/Canadian musician who was well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 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.066
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0660.019

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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2023
Admission routes1
Has abstractyes

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