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Record W1166500989

Musikiosk: a soundscape intervention and evaluation in an urban park

2015· article· en· W1166500989 on OpenAlexaboutno aff
Daniel Steele, Romain Dumoulin, Louis Voreux, Nicolas Gautier, Mathias Glaus, Catherine Guastavino, Jérémie Voix

Bibliographic record

VenueEspace ÉTS (ETS) · 2015
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
Fundersnot available
KeywordsSoundscapeUrban parkIntervention (counseling)MicrophonePerspective (graphical)Sound (geography)Environmental resource managementEnvironmental planningArchitectural engineeringComputer scienceGeographyEngineeringPsychologyEnvironmental scienceTelecommunicationsAcoustics
DOInot available

Abstract

fetched live from OpenAlex

Musikiosk is an interactive music installation and environmental monitoring station developed for urban parks by \nCIRMMT, ÉTS, McGill, and the City of Montreal. We describe the development of the technology and propose a \ncomprehensive mixed-methods research program to evaluate its impact on the community. Environmental monitoring \nvia an ambient microphone input provides information about system usage, physical measurements of the acoustic \nenvironment, and playback levels. A survey with park users, non-users, and residents will be conducted before and after \nthe installation to empirically evaluate the urban sound intervention and best integrate the users’ perspective throughout \nits lifecycle. Findings will contribute toward theories on the roles of activity and music in soundscape evaluations and \nwill be among the firsts to observe changes in a manipulated soundscape. Parties that stand to benefit are park users, \nresidents, researchers, and the city for various reasons.

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)0.005
metaresearch head score (Gemma)0.007
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 score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.073
GPT teacher head0.422
Teacher spread0.349 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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