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Record W2049101172 · doi:10.1504/ijplm.2014.065457

Concurrent versioning principles for collaboration: towards PLM for hardware and software data management

2014· article· en· W2049101172 on OpenAlexaff
Matthieu Bricogne, Louis Rivest, Nadège Troussier, Benoît Eynard

Bibliographic record

VenueInternational Journal of Product Lifecycle Management · 2014
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsApplication lifecycle managementProduct lifecycleSoftware versioningSoftware engineeringSoftwareMerge (version control)Product data managementSystems engineeringComputer scienceData managementEngineeringNew product developmentDatabaseOperating system

Abstract

fetched live from OpenAlex

The change management (CM) and version control mechanisms used in the mechanical and software domains are presented in the product lifecycle management (PLM) and application lifecycle management (ALM) approaches, respectively. Based on their comparison, this paper discusses branching/merging concepts and utilises them to propose an evolution of the product data management (PDM) functions of PLM, thereby allowing PLM to become a collaborative platform common to software and hardware engineers. This evolution is an opportunity to develop a three-way merge tool for CAD documents. Recent works on model-merging techniques from the software development domain are evaluated in the process.

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)0.017
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.017
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.024
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0020.007
Scholarly communication0.0090.015
Open science0.0050.010
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.278
Teacher spread0.251 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations13
Published2014
Admission routes1
Has abstractyes

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