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Record W2041815803 · doi:10.1115/detc2008-49542

A Unified Framework for Decomposition of Design Structure Matrix and Domain Mapping Matrix

2008· article· en· W2041815803 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsDesign structure matrixComputer scienceDecompositionDependency (UML)Context (archaeology)Domain (mathematical analysis)WorkflowMatrix (chemical analysis)Matrix decompositionTheoretical computer scienceAlgorithmSoftware engineeringMathematicsSystems engineeringEngineeringDatabase

Abstract

fetched live from OpenAlex

In literature, design structure matrix (DSM), which is a square matrix, has been widely used to address single-domain dependency relationships (e.g., product architecture, process workflow, and organization structure). To extend the DSM efforts, a rectangular matrix becomes a logical format to capture and analyze cross-domain dependency relationships, namely, domain mapping matrix (DMM) [1]. In this context, this paper proposes a unified framework for decomposition of DSM and DMM. The unified framework consists of four methodological phases to offer the functions of DSM clustering, DSM sequencing, and DMM decomposition. To support the development of this framework, various decomposition-related techniques from applied mathematics and engineering design are reviewed. Three matrix examples have been used to illustrate the framework’s applicability.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.371
Threshold uncertainty score0.405

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 head0.021
GPT teacher head0.252
Teacher spread0.231 · 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

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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