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Record W7095211576

Design Competition Report Cougar Shadow Human Powered Vehicle Team Report Prepared by:

2016· article· en· W7095211576 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsFrame (networking)Suspension (topology)Design for manufacturabilityPlan (archaeology)Finite element methodParametric statisticsConceptual designDependency (UML)Product (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

Washington State University Vancouver entered the 2007 HPVC with a reverse three wheel recumbent design. This vehicle had some good features. The 2008 team decided to make several improvements to the existing vehicle; some of which are: a new carbon-fiber fairing, simplified rear suspension, stronger front suspension, highly adjustable pedal position, and larger chain ring. The decisions to implement these changes were arrived at through the use of weighted rating matrices, expert advice from bicycle professionals, and mathematical analysis. Some of the initial choices were later changed due to further introspection following consul-tation with experienced advisers. In particular, the original plan to create a new frame with chrome moly tubing was eliminated when it was obvious that the manufacturability was difficult and our time would be better spent modifying the existing aluminum frame. Conceptual designs were made using SolidWorks parametric modeling software. COSMOS FloWorks was used to assess the aero-dynamic characteristics of our fairing design. Finite Element Analysis of the frame and suspension components was carried out with COSMOS and in some cases with ANSYS. Stress testing with an Instron machine was used to verify the critical components and to check the strength of our welds. Two iterations of our fairing design were also tested in a water tunnel to visualize the fluid flow in order to reduce the turbulence and thereby decreasing the drag. The resulting vehicle performance is expected to be a significant improvement over the existing design. Construction is currently under way and tests of the final product will prove our design. We will make modifications to correct any problems encountered and

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)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.238
Threshold uncertainty score0.795

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0040.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.2380.128

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 head0.025
GPT teacher head0.289
Teacher spread0.263 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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