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Record W2016772609 · doi:10.1121/1.4785028

A comparison of different expression devices in pipe organs

2004· article· en· W2016772609 on OpenAlexaff
Jonas Braasch, Thomas D. Rossing

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2004
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
Fundersnot available
KeywordsSwellRange (aeronautics)AcousticsGeologyPhysicsEngineeringAerospace engineeringOceanography

Abstract

fetched live from OpenAlex

After the introduction of the orchestra crescendo at the end of the 18th century by the ‘‘Mannheim school,’’ the ability to play the organ expressively like an orchestra was one of the organ builders’ greatest concerns. Soon, both the wind swell and door swell came into fashion, and later another swell system, the crescendo wheel, was introduced. While both door swell and crescendo wheel can be successfully applied to all types of organ stops, the wind swell only works well with free reeds for tuning reasons. In this investigation, all three swell systems were measured on various instruments and compared to each other. In addition, two free-reed pipes were measured at the Northern Illinois University using a laser vibrometer. The crescendo wheel was found to be most effective, and for frequencies around 2 kHz the increase in sound-pressure level could be up to 50 dB between the softest and the loudest adjustment. The maximum dynamic range for the wind and the door swells is approximately 10 dB in the same frequency range. While the dynamic range is lower for the wind swell and the door swell, their advantage is the continuous variability.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.280
Teacher spread0.263 · 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 designObservational
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
Published2004
Admission routes1
Has abstractyes

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