MétaCan
Menu
Back to cohort
Record W4320734122 · doi:10.3397/in_2022_0787

The Vibration Reduction Index of Typical Canadian Cross-laminated Timber Junctions

2023· article· en· W4320734122 on OpenAlexaffabout
Jeffrey Mahn, Markus Müller-Trapet, Iara Batista da Cunha

Bibliographic record

VenueNOISE-CON proceedings · 2023
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsVibrationReduction (mathematics)Noise (video)Index (typography)Research councilCode (set theory)Empirical researchTransmission (telecommunications)Sound transmission classEngineeringComputer scienceCivil engineeringTelecommunicationsAcousticsPhysicsMathematicsStatistics

Abstract

fetched live from OpenAlex

In support of the National Building Code of Canada, The National Research Council Canada has published research report RR-335 which describes the results of measurements of the transmission of structure-borne noise through junctions between mass timber elements. The Code only allows for the use of measured data for the vibration reduction index from the NRC's reports or reports from other research institutes. The Code does not currently allow for the use of empirical data for the calculation of the apparent sound transmission class of mass timber buildings. A lack of published data for typical mass timber junctions used in Canada can result in the overdesign of buildings or buildings which don't meet the acoustic requirements of the Code. The NRC has embarked on a program to measure the vibration reduction index of a number of mock junctions of typical junctions used in Canada including junctions between cross-laminated timber floors and lightweight timber framed walls. The new data will aid in the development of empirical models of typical Canadian mass timber constructions.

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)0.000
metaresearch head score (Gemma)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.222
Teacher spread0.215 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueNOISE-CON proceedingsSame topicStructural Engineering and Vibration AnalysisFrench-language works237,207