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Record W2133850799 · doi:10.1109/noms.2004.1317770

Web Service Offerings Infrastructure (WSOI) - a management infrastructure for XML Web services

2004· article· en· W2133850799 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceWS-PolicyWeb serviceWorld Wide WebXMLService (business)SOAPDatabaseWeb developmentBusinessWeb application security

Abstract

fetched live from OpenAlex

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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.001
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 head0.004
GPT teacher head0.209
Teacher spread0.205 · 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