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Record W1998529837 · doi:10.1109/ictai.2006.40

Classifying Business Processes for Domain Engineering

2006· article· en· W1998529837 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

VenueProceedings - International Conference on Tools with Artificial Intelligence, TAI · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsComputer scienceBusiness processBusiness process modelingSoftware engineeringArtifact-centric business process modelEclipseBusiness ruleBusiness domainDomain (mathematical analysis)Business Process Model and NotationFunctional software architectureSystems engineeringSoftwareProcess managementSoftware architectureProgramming languageEngineeringWork in processReference architecture

Abstract

fetched live from OpenAlex

Enterprises build information systems to support their business processes. Some of those business processes are industry or enterprise-specific, but most are common to many industries and are used, modulo a few modifications, in different contexts. To the extent that we can, i) decompose complex business processes into composable generic sub-processes, ii) develop software components that implement such generic processes, and iii) map process specialization and composition operators to corresponding operators on software components, we will be able to develop information systems by modeling the business processes that they are meant to support, and using such models to guide the assembly of the corresponding software components. This is not a new idea, but earlier attempts suffered from the lack of tools, conceptual and otherwise, to perform this mapping. In this paper, we describe the principles underlying our approach and the status of the current implementation in the Eclipse environment.

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 categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.695
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.000
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 head0.077
GPT teacher head0.267
Teacher spread0.190 · 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