MétaCan
Menu
Back to cohort

Systems Engineering – The Hard Way

2018· article· en· W2912184262 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueConference Proceedings of INEC · 2018
Typearticle
Languageen
FieldEngineering
TopicTechnology Assessment and Management
Canadian institutionsnot available
FundersLoughborough UniversityYork University
KeywordsObsolescenceRisk analysis (engineering)Context (archaeology)Process (computing)Computer scienceEngineering design processNaval architectureClass (philosophy)Systems engineeringEngineeringBusiness

Abstract

fetched live from OpenAlex

Ship designers, builders, owners, insurers and class societies are becoming ever more aware of the complex interactions of the various systems found on all types of marine vessels. Therefore a design process that acknowledges these demands and assesses the risks posed, and manages them becomes ever more important. This paper seeks to explore some of the, sometimes apparently, conflicting requirements that are placed on designs of new marine platforms and looks at methods that enable these elements to be expressed, understood and managed in the context of an integrated ship design. The demands placed on new vessels include a range of requirements that move away from being solely based around the traditional functional requirements; including the ideas of designing for ease of shipbuilders, operators and maintainers; and now acknowledging the need of a through life safety case, cyber security case, and full obsolescence planning. This becomes ever more complex when consideration is given to how these through life elements are practically managed, with a range of methods, none of which are without their own challenges. It is important to note as these demands are discussed that often a ‘solution’ in the truest sense does not exist and the management of risk becomes a balance between the expected risk, the practicable solution, along with the potential compromises to both programmes and cost. While these demands place huge constraints and drive complexity into design processes, the issues can, and regularly have, been further exacerbated when some of these, or other requirements, are introduced into the design or build phases of projects. Introduction of design drivers should not be undertaken lightly or without expected, and accepted, increases in required resources, both financial and calendrical.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.197
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