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Record W1888875491 · doi:10.24908/pceea.v0i0.3895

THE CONTRIBUTION OF INDUSTRY TO SHIP DESIGN EDUCATION

2011· article· en· W1888875491 on OpenAlexaffvenue
J. Mikkelsen, Sander M. Çalışal

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCapstoneNaval architectureEngineering managementCompetition (biology)EngineeringArchitectureProcess (computing)ShipbuildingEngineering design processDesign educationDesign processIterative designDesign briefOrder (exchange)Software engineeringComputer scienceSystems engineeringDesign technologyOperations managementWork in processBusinessMarine engineering

Abstract

fetched live from OpenAlex

This paper details the Naval Architecture program at the University of British Columbia with emphasis on the delivery of the capstone design program in ship design. Since the enrollment is a small number of highly motivated students, the program instructors can utilize innovative project based learning strategies into the program. The paper highlights the iterative nature of ship design that is traditionally represented by a design spiral. In order to reinforce relevance and ensure that practices parallel those of industry, the instructors of the computer aided ship design course rely on the local Naval Architecture design firms to provide assistance to the students. This assistance is in the form of mentorship, access to proprietary design data and software, and student evaluation. In addition, the course instructors require that the student design teams complete a ship design that meets the requirements of an industry sponsored design competition. The paper illustrates the ship design process with an example of a student ship design project entered into an international competition.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.215
Teacher spread0.199 · 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 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

Citations1
Published2011
Admission routes2
Has abstractyes

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