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Record W2038524011 · doi:10.1115/detc2010-28464

A Conflict Detection Approach for Collaborative Management of Product Interfaces

2010· article· en· W2038524011 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 institutionsMcGill University
Fundersnot available
KeywordsComputer scienceConsistency (knowledge bases)Interface (matter)Representation (politics)Process (computing)Product (mathematics)User interfaceSoftware engineeringSystems engineeringArtificial intelligenceEngineeringProgramming language

Abstract

fetched live from OpenAlex

In complex products, maintaining subsystem consistency throughout the design process is often a time-consuming process of document exchange among cooperating functions. This paper describes a conflict management approach that lead to the computer-aided management of the product specification conflicts that happen due to the integration of subsystems. In order to define a framework, a systematic interface representation which proposes building generic interface schemes for subsystem connectivity representation is described. Based on this methodology, a functional architecture of the proposed conflict management method, along with generic exception taxonomy of conflicts is developed. The applicability of the proposed concepts is discussed through illustrative examples. The proposed methodology is intended to allow automatic detection and handling of interface connectivity errors throughout collaborative design processes.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.364

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 communication0.0000.001
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 head0.017
GPT teacher head0.223
Teacher spread0.206 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

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