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Record W2072598928 · doi:10.1115/msec2013-1231

Progressive Modeling and the Reconfiguration and Operations Planning Problem

2013· article· en· W2072598928 on OpenAlex
Mohamed A. Ismail

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
FieldEngineering
TopicFlexible and Reconfigurable Manufacturing Systems
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsControl reconfigurationComputer scienceSPARK (programming language)Process (computing)Systems engineeringIndustrial engineeringEngineeringEmbedded system

Abstract

fetched live from OpenAlex

In this paper, the progressive modeling approach and the Reconfiguration and Operation Planning (ROP) problem are introduced. Progressive Modeling (PM) is a forward-looking multi-disciplinary modeling approach that has been developed to modernize the modeling process of today’s complex industrial problems and create pragmatic solutions for many of them. Many principles and foundations of progressive modeling will be presented while utilizing the reconfiguration and operation planning problem (ROP) as a demonstrating application. The ROP problem describes a new approach of reconfiguration and operations planning in a reconfigurable manufacturing environment. PM is about to spark a new paradigm of solving large-scale system problems in many engineering and business domains in a highly pragmatic way without losing the scientific rigor.

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 score0.064
Threshold uncertainty score0.229

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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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