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Record W1537281386

Alarmlocator: A software tool to facilitate the installation of acoustic warning devices in noisy work plants

2006· article· en· W1537281386 on OpenAlexaffvenue
Rida Al Osman, Christian Glguère, Chantal Laroche

Bibliographic record

VenueCanadian acoustics · 2006
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsWorkstationInstallationSoftwareComputer scienceProcess (computing)Ceiling (cloud)Work (physics)EngineeringOperating systemMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Alarmlocator, a software tool was developed to facilitate the process of installing auditory warning devices in noisy work plants. It was found that the software tool produced a solution to two practical installation problems such as a suitable number of warning devices and their acoustic power for a given work area and specifying the location of the devices in the plant in such a way that the signals emitted are clearly audible by all workers and at all workstations. The general modeling framework proposed for the optimal installation of warning devices consisted of the integration of two software tools, Detectsound and Alarmlocator. The Alarmlocator accounted for the sound propagation of warning signals from the physical device location to the position of individual workers or workstations. The model of the device has taken into account the direct field from the alarm devices and the reverbant field due to wall, ceiling, floor, and other reflections.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.004

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 head0.011
GPT teacher head0.180
Teacher spread0.169 · 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 designBench or experimental
Domainnot available
GenreSoftware

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
Published2006
Admission routes2
Has abstractyes

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