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Record W2077414333 · doi:10.1121/1.4877944

Designing an auditory lab including active acoustics

2014· article· en· W2077414333 on OpenAlexaff
Ranil Sonnadara, Steve Ellison, Laurel J. Trainor, Dan Bosnyak

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2014
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsReverberationQUIETAcousticsComputer scienceInstrumentation (computer programming)Room acousticsPhysics

Abstract

fetched live from OpenAlex

LIVELab, a new facility at McMaster University, has been developed in order to help support research in areas such as developing intelligent hearing aids, measuring the physiological impact of media presentations, understanding interactions between musicians, and determining effective sounds for medical and warning systems. This room combines a quiet performance space featuring a low nominal reverberation time with technology including active acoustics, multichannel playback, and integral measurement and instrumentation to create a sonically flexible facility for auditory research. The design of the room and its acoustic variability for supporting these research endeavors will be discussed.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.895
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.368
Teacher spread0.328 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2014
Admission routes1
Has abstractyes

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