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Record W2226100936 · doi:10.4271/2008-01-1103

Back-Calculated Spindle Loads Sensitivity to Suspension Component Loads Availability

2008· article· en· W2226100936 on OpenAlexaff
Xiaobo Yang, Yongxin Men, Michael N. Rowley

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2008
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsChrysler (Canada)
Fundersnot available
KeywordsSensitivity (control systems)Component (thermodynamics)Suspension (topology)Computer scienceStructural engineeringControl theory (sociology)Automotive engineeringEngineeringElectronic engineeringPhysicsMathematics

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">In this study, two common types of suspension are used to study back-calculated spindle loads sensitivity to the availability of suspension component loads, under a severe loading proving ground event. The previously back-calculated spindle loads (Targets) are initially used as the inputs to resolve suspension component loads, which are considered as the “perfectly measured data”. With full factorial design of experiments (DOE), the back-calculated spindle loads using the known suspension component loads are then compared with the targets to produce the sensitivity of the spindle loads in comparison with the suspension components.</div>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.021
GPT teacher head0.249
Teacher spread0.229 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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
Published2008
Admission routes1
Has abstractyes

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