INCREASING INTEROPERABILITY WITH CEONET TECHNOLOGY USING WSDL AND
Bibliographic record
Abstract
The future World Wide Web will be composed of interoperable, distributed software components called Web Services. These services will be capable of automatically discovering and invoking one another, allowing complex applications to be created from collections of interacting Web Services. Two new Web technologies that help make this possible are Web Services Description Language (WSDL) and the Simple Object Access Protocol (SOAP). A network of interoperable Web Services that dynamically interact with one another to perform a host of geoprocessing activities will likely form the technological building blocks enabling the next generation of Spatial Data Infrastructures. Although CEONet Technology already provides programmatic access to its services, this access is based on a mix of proprietary and standard mechanisms. Recasting CEONet Technology and its partners as a collection of Web Services that use WSDL and SOAP would increase interoperability in the Canadian Geospatial Data Infrastructure while reducing dependencies on proprietary technology. This paper describes WSDL and SOAP and how they can be used to transform CEONet Technology from a web application to a collection of standards-based, interoperable Web Services. 1.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".