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Record W6996176818

RC Baja Steering and Suspension

2024· article· en· W6996176818 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks (Central Washington University) · 2024
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsnot available
Fundersnot available
KeywordsSuspension (topology)USableCar modelFront (military)Quarter (Canadian coin)Automobile handlingAutomotive industryProcess (computing)
DOInot available

Abstract

fetched live from OpenAlex

The engineering objective of this project are designing, manufacturing, and testing the most efficient and strongest possible RC Baja Steering and Suspension system that the engineer could produce with the provided or acquired equipment, and materials. This was all done successfully over the school year. During the Fall quarter, the RC car was undergoing designing, and in these design processes, mechanics of materials, statics, and dynamics, were used to come up with the most adequate materials and design. Computer aided designed (CAD) models were then created to get a RC Baja CAD assembly. Winter Quarter of the school year was the manufacturing, and construction process of each and individual part for the RC car. Spring quarter of the RC Car was testing of the entire car to confirm whether the car satisfies the requirements stated in the beginning of the quarter or not. In the suspension components, the front and rear suspension was to have a 2” articulation. Along with this, the car was listed to have a usable 1” of suspension travel front and rear under its own static weight. It was also noted that that the car needed to make a 180 degree turn in a 3.5’ radius, and the car completed this in only a 2’ radius, almost a 60% tighter turning radius. After all the research was done, the car met all requirements. Each part of the car met or exceeded the initial requirements made by the engineer.

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 score0.537
Threshold uncertainty score0.596

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.193
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 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
Published2024
Admission routes1
Has abstractyes

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