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Record W1911316101 · doi:10.24908/pceea.v0i0.4014

A GRAPHICS AND DESIGN COURSE BASED ON COMPETITION MACHINE DEVELOPMENT

2011· article· en· W1911316101 on OpenAlexaffvenue
Marek Kujath, Ted Hubbard

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicMechatronics Education and Applications
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCONTESTCourse (navigation)Competition (biology)Computer scienceTask (project management)GraphicsSoftware engineeringEngineering managementEngineeringSystems engineeringComputer graphics (images)

Abstract

fetched live from OpenAlex

A second year mechanical engineering course in design and graphics is described. The course is structured around the design and fabrication of machines that take part in a competition at the end of the term; however, the main components of the students' performance evaluation are midterm and final design reports. The design objective is to build a competition machine, using only a supplied kit of materials, that performs a specified task better than the opponent’s. The course instructor prepares a new contest each year. This paper outlines the course structure and contents. It details the competition organization and its physical setup. Challenges associated with teaching this type of design course are discussed as well.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.085
Threshold uncertainty score0.283

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0850.029

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 head0.012
GPT teacher head0.187
Teacher spread0.175 · 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
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
Published2011
Admission routes2
Has abstractyes

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