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Record W2987355656

Reformulating Burmese Harp Tunings

2019· other· en· W2987355656 on OpenAlexaff
Jay Rahn

Bibliographic record

VenueYork University Digital Library (York University) · 2019
Typeother
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHARPBurmeseComputer scienceArtificial intelligenceHistoryPhilosophyLinguistics
DOInot available

Abstract

fetched live from OpenAlex

Distinctive in shape, size, construction and playing position, the Burmese harp has been traditionally tuned by ear; that is, without the intervention of a monochord or more recent devices, such as electronic tuners. In the latter regard, it is similar to harps and lyres of Antiquity: in Mesopotamia about four millennia ago, Ancient Greece more than 2300 years ago, and Ancient India about 1700 years ago. Also of plausible relevance to Burmese harp tuning are tunings of fixed-frequency instruments of other Southeast Asian traditions: of Central Java and Thailand, for example. Although such xylophones and metallophones have also been tuned by ear and employed in Burmese classical music along with the harp, the inharmonic spectra of their tones differ from the harmonic spectra produced by the open strings of the harps and lyres just mentioned. In particular, open strings produce predictable beats when plucked simultaneously.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.264
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0030.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.009
GPT teacher head0.154
Teacher spread0.145 · 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
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

Citations1
Published2019
Admission routes1
Has abstractyes

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