MétaCan
Menu
Back to cohort
Record W6966589367 · doi:10.4224/40003487

Management and correction of wind-measurement biases on long-span bridges: model geometry for a 1:100-scale bridge

2025· dataset· en· W6966589367 on OpenAlexaffabout

Bibliographic record

VenueNRC Digital Repository · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsBridge (graph theory)Research councilMeasure (data warehouse)AerodynamicsDistortion (music)Wind tunnel

Abstract

fetched live from OpenAlex

The Aerodynamics Laboratory at National Research Council Canada (NRC) is engaged in a multi-year project through its Climate Resilient Built Environment program to provide guidance and best practices for predictive environmental models for bridge-monitoring systems. In support of the objective to improve the accuracy of wind-monitoring systems, the NRC conducted a wind-tunnel study to measure the bridge-induced distortion to the wind vector in proximity to a bridge. Wind-velocity profiles were acquired in proximity to a 1:100-scale bridge model in the NRC 1.0 m × 0.8 m Pilot Wind Tunnel. The computer-aided design (CAD) geometry file for the 1:100-scale bridge model is available for download. This research data entry includes a descriptive document and a 3D CAD model.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0040.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0260.040

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 head0.035
GPT teacher head0.271
Teacher spread0.236 · 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 designSimulation or modeling
Domainnot available
GenreDataset

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
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueNRC Digital RepositoryFrench-language works237,207