Bibliographic record
Abstract
With the support of user configurable high speed networks, the emerging e-Infrastructure allows seamless sharing of expensive scientific resources. These resources are often running on a variety of platforms, have different bandwidth and QoS requirements, require specific configuration by technical experts, and in most cases cannot be accessed through a single point of entry. To address these issues, we propose an extensible, reliable, and simple software architecture to share the applications and resources over hybrid networks, and hide the tools' logistical and provisioning complexities. This paper explores the design and implementation of Eucalyptus, and describes how it leverages the benefits of a Service-oriented Architecture (SoA) to provide a highly adaptable, modular, and loosely coupled solution to configure and manage resources needed by users collaborating over the net. We present our methodology to wrap functions of resources into Web services, and integrate the new Web services into the Eucalyptus platform in a generic way. The streams of the events from these resources are captured. This information is used for monitoring resources' activities and diagnosing any error that may arise. We provide a workflow management service allowing users to orchestrate services based on the description of the resources, their dependencies and the captured streams to perform certain tasks. We also propose a combination of Web services and peer to peer technologies to support users in different communities and different network layers, and to decentralize resource management. Eucalyptus was demonstrated to be effective in assisting architects across multiple sites to effectively participate in a shared design session.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".