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Record W2472162277

Pliteq Inc. – 2015 Research in Architectural Acoustics

2016· article· en· W2472162277 on OpenAlexvenueaboutno aff
Wilson Byrick, Matthew V. Golden

Bibliographic record

VenueCanadian acoustics · 2016
Typearticle
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsnot available
Fundersnot available
KeywordsEngineeringFrame (networking)AcousticsStiffnessStructural engineeringVibration isolationSound (geography)Architectural engineeringVibrationMechanical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

Pliteq Inc. est une société d'ingénierie basée à Toronto spécialisée en acoustique architecturale.Le PDG Paul Downey est répertorié comme l'inventeur de 7 brevets d'atténuation liées au son et aux vibrations.Les lignes de produits GenieMat TM et GenieClip TM sont testés pour leur efficacité sur différentes structures pour diverses applications utilisant des laboratoires tiers indépendants et des procédures de test tel que définie par l'ASTM.En 2015, plusieurs programmes d'essais furent complétées, les résultats sont présentés dans cet article.Les sujets de recherche inclus l'évaluation de la performance de; GenieMat TM FIT produits de revêtement de sol pour l'isolation contre les impacts lourds, l'utilisant d'un système de plusieurs couches de GenieMat TM FF pour obtenir une faible fréquence naturelle et une rigidité dynamique des planchers flottants, en utilisant la GenieClip TM pour réduire les bruits d'impact dans la construction à ossature de bois et, enfin, en utilisant tous les types de produits mentionnés ci-dessus pour réduire la transmission des bruits d'impacts et sons aériens dans les construction utilisant le bois lamellé-croisé (CLT).

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score0.442

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0020.002
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1320.043

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 head0.033
GPT teacher head0.286
Teacher spread0.253 · 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 designNot applicable
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
Published2016
Admission routes2
Has abstractyes

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