Service-Oriented Enterprises and Architectures: State of the Art and Research Opportunities
Bibliographic record
Abstract
To survive in the global marketplace, organizations need to continually adapt to the changing business environment. Information systems play an ever increasing role in helping organizations achieve this objective. Recently, there has been considerable attention paid to the service orientation and how it could alter the way organizations function and their relationships with business partners such as suppliers. In this research, we focus on service-oriented enterprises and architectures. In doing so, we bring to the fore the current state of the art in the emerging service paradigm. Service-oriented computing is revolutionizing the way corporations manage information so as to enable streamlining the various stages of computing including strategic planning, business process management, operations processing, and information technology services. We demonstrate how the application of service orientation to a supply chain will lead to service-centric supply chains that offer significantly more enterprise agility. We also discuss opportunities for future research in the new paradigm.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.014 | 0.032 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".