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Record W2109336405 · doi:10.1504/ijeb.2013.051416

Application framework support for process-oriented software development

2013· article· en· W2109336405 on OpenAlexaffabout
Abel Tegegne, Liam Peyton

Bibliographic record

VenueInternational Journal of Electronic Business · 2013
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceProcess managementWorkflowProcess (computing)Business processSoftware engineeringBusiness process managementSoftware development processSoftware developmentBusiness process modelingSoftwareSystems engineeringWork in processDatabaseEngineeringOperations management

Abstract

fetched live from OpenAlex

As organisations move their business processes online, it is becoming important for software development to be process-oriented. In particular, managed process applications are a class of business software that helps to improve operational efficiency in organisations by monitoring processes and reporting on performance. General purpose application development tools and model-driven architecture do not support run-time configurability of a managed process nor do they provide specific systematic support for integrated data collection, monitoring and reporting within a managed process. To facilitate such configurability and integrated data management, a model-based application framework is needed to address process-oriented software development. In this paper, we describe a prototype of such a framework, illustrating and evaluating the benefits, with a case study of a system developed for and used by a palliative care support team in Ottawa, Canada. In the case study, we illustrate how a managed process can be modelled using the prototype framework (including its’ workflow, roles, entities, events, alerts and performance indicators).

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)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.011
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0050.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.005

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 head0.005
GPT teacher head0.252
Teacher spread0.248 · 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 designNot applicable
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

Citations3
Published2013
Admission routes2
Has abstractyes

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