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Record W2046276915 · doi:10.1177/1063293x15571759

A study of overlapping and functional interaction mechanisms for concurrent engineering processes

2015· article· en· W2046276915 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

VenueConcurrent Engineering · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsConcordia UniversityMcGill University
Fundersnot available
KeywordsBaseline (sea)Computer scienceProcess (computing)Sensitivity (control systems)Interaction modelEngineering

Abstract

fetched live from OpenAlex

This article reports the use of a stochastic computer model to study hybrid overlapping and functional interaction strategies, where, within a given process, different degrees of overlapping or gradually increasing or decreasing functional interaction were modeled. The study aims to understand the contribution of these strategies to process performance, that is, product development effort and span time. Simulation results of the hybrid models are discussed in comparison to a baseline model, where the baseline process was uniformly overlapped and functional interaction was constant throughout its execution. Research outcomes indicate that under high information uncertainty, sequential processes perform better than any model with overlap. When uncertainty is moderate or low, the baseline model outperforms the hybrid models. Under high sensitivity conditions, hybrid overlapping models perform equally well in comparison to the baseline model with complete overlap, and superiorly when information evolution is slow.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.718

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 head0.043
GPT teacher head0.230
Teacher spread0.186 · 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