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Record W2013746192 · doi:10.1177/1077546311426250

Development, validation, and parameter sensitivity analyses of a nonlinear mathematical model of air springs

2011· article· en· W2013746192 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Vibration and Control · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Environments and Student Outcomes
Canadian institutionsUniversity of OttawaRoyal Military College of CanadaUniversity of Waterloo
Fundersnot available
KeywordsNonlinear systemSensitivity (control systems)Mathematical modelLinear modelNonlinear modelNonlinear modellingEngineeringControl theory (sociology)Computer scienceMathematicsPhysicsElectronic engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Air springs are highly nonlinear devices. Linear and quasi-linear models of air springs have been developed over the years to analyze and predict their behavior. Such models are shown here to be inadequate to describe the behavior of this highly nonlinear element. A nonlinear mathematical model of air springs has been developed and reported in this paper. The model has been verified experimentally, and has been shown to be effective in predicting the behavior of air springs. The sensitivity of the model to uncertainties in two key parameters is examined.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.117

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.082
GPT teacher head0.347
Teacher spread0.265 · 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