Introduction to the Proceedings of the EDOC 2006 Workshop Middleware for Web Services (MWS) 2006
Bibliographic record
Abstract
Welcome to the Proceedings of the EDOC 2006 workshop Middleware for Web Services (MWS) 2006! The workshop is a follow-up to the successful MWS 2005 workshop held at the EDOC 2005 conference and the subsequent special issue of the International Journal of Business Process Integration and Management (IJBPIM, published by Inderscience Publishers). Similarly to these past venues, the MWS 2006 workshop is sponsored by the National Information and Communications Technology Australia (NICTA). During the past several years, Web services technologies have become very prominent in both the research community and the industry. Web services are distributed computing application components implementing the service-oriented architecture (SOA). They rely on Extensible Markup Language (XML) interface description languages, such as the standardized Web Services Description Language (WSDL), and communication protocols, such as the standardized SOAP protocol (previously known as the Simple Object Access Protocol). In addition, Web services can use a number of other standardized and/or proprietary XML-based formats, such as the standardized Web Services Business Process Execution Language (WSBPEL) for describing business processes implemented as Web service compositions. Implementation-independence of Web services technologies allows different businesses to collaborate and achieve common business goals despite the fact that the collaborating Web services can be distributed over the Internet, run on different platforms, and implemented in different programming languages. Web services technologies are already embedded in various products and services of all major computing companies and used for diverse purposes.
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 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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.211 | 0.160 |
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".