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Record W4379877246 · doi:10.2514/6.2023-3894

The enduring role of TASK balances in wind tunnel testing at the National Research Council Canada

2023· article· en· W4379877246 on OpenAlexaffabout
Heather Clark, Jean-Eric Sink, Marc MacMaster

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsTask (project management)Wind tunnelSoftware deploymentResearch councilWork (physics)AerodynamicsCalibrationAeronauticsBalance (ability)Computer scienceEngineeringOperations researchSystems engineeringMechanical engineeringAerospace engineeringPsychologyGovernment (linguistics)Software engineering

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2023-3894.vid The historical and continued role of TASK internal strain-gauge balances in the work of the National Research Council Canada (NRC) is presented. From the late 1950s onward, the NRC inventory of TASK balances expanded in response to the diverse and increasingly complex requirements of wind tunnel research and client testing. TASK balances have been especially integral to the measurement of aerodynamic loads at the 1.5 m TrisonicWind Tunnel, as illustrated through examples of historical and recent applications, and in the calibration equipment used to enable their continued deployment. Decades of experience at the NRC resulted in meaningful contributions to the collaborative development of recommended practices for the calibration and use of internal balances, to the benefit of the wider wind tunnel testing community. An overview of ongoing work toward the improvement of NRC balance calibration capabilities is provided.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.074
GPT teacher head0.259
Teacher spread0.185 · 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 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

Citations1
Published2023
Admission routes2
Has abstractyes

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