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Record W3051936404 · doi:10.1016/j.procir.2020.02.169

Objective based process model for enhancing the product maturity level in the early phase of a development process

2020· article· en· W3051936404 on OpenAlexaff
Thilo Richter, David B. Schmidt, Holger Hahlweg, Kamran Behdinan, Albert Albers

Bibliographic record

VenueProcedia CIRP · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProcess (computing)Process managementNew product developmentSelection (genetic algorithm)Systems engineeringProcess modelingPhase (matter)Computer scienceProduct (mathematics)EngineeringCapability Maturity ModelIndustrial engineeringManagement scienceWork in processOperations managementArtificial intelligenceSoftwareBusinessMathematics

Abstract

fetched live from OpenAlex

In the early phase of a development process, several concept variations are developed to overcome technical problems. Despite this, only one concept makes the final selection. In this study, a theoretical process model providing an early-phase, structured proceeding guideline was adapted for use in a development process in order to simplify concept selection. This adapted process model enables a more time-efficient and transparent early-phase development process. Furthermore, it presents an opportunity for the relationship between design engineers and simulation engineers to be improved. The adapted process model was validated by using a combination of simulated models and expert interviews.

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)0.003
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.052
GPT teacher head0.274
Teacher spread0.222 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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