Web Service Offerings Infrastructure (WSOI) - a management infrastructure for XML Web services
Bibliographic record
Abstract
Our Web Service Offerings Language (WSOL) enables formal specification of important management information - classes of service (modeled as service offerings), various types of constraint (functional, QoS, access rights), and management statements (e.g., prices, penalties, and management responsibilities) - for XML (Extensible Markup Language) Web services. To demonstrate the usefulness of WSOL for the management of Web services and their compositions, we have developed a corresponding management infrastructure, the Web Service Offerings Infrastructure (WSOI). WSOI enables monitoring and accounting of WSOL service offerings and their dynamic manipulation. To support monitoring of WSOL service offerings, we have extended the Apache Axis open-source SOAP engine with WSOI-specific modules, data structures, and management ports. To support dynamic manipulation of WSOL service offerings, we have developed appropriate algorithms, protocols, and management port types and built into WSOI modules and data structures for their implementation. Apart from provisioning of WSOL-enabled Web services, we are using WSOI to perform experiments comparing dynamic manipulation of WSOL service offerings and alternatives.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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.
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".