Performing distributed simulation with RESTful Web-services
Bibliographic record
Abstract
Distributed simulations are mainly used to interoperate heterogeneous simulators or geographically distributed models. We present here RESTful-CD++, the first distributed simulation middleware based on REST (Representational State Transfer) Web-services. RESTful-CD++ middleware enables heterogeneous independent-developed simulation components to interoperate with much flexibility and simplicity. REST has the potential to advance distributed simulation state-of-the-art towards plug-and-play or automatic/semi-automatic interoperability. This because of its lightweight approach hides internal software implementation by using universal uniform interface and describing connectivity semantics in form of messages, usually XML. In contrast, other approaches expose functionalities in heterogeneous RPCs that often reflect internal implementation and describe semantics in form of procedure parameters. Further, REST enables simulations to mashup with Web 2.0 applications, which makes simulation in link with any device attached to the Web dynamically at runtime. The CD++ tool is now the first simulation engine to use RESTful middleware to perform distributed simulation in large-scale.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.007 |
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".