A General Framework for Web Services and Grid-Based Technologies for Online Laboratories
Bibliographic record
Abstract
The combination of Web Services and grid-computing technologies is currently of a major scientific revolution. It combines the middleware solution from Web Services and resource-sharing solutions of grid computing. We present a general framework based on Web Services and grid-based technologies for online laboratories. It is a distributed system model where computational resources and experimental devices throughout the networks are organized into federations. The benefits of this model are information processing capacity increase and resource sharing. We discuss a number of technical considerations using this framework. These include: the descriptions of tele-experimentation resources; the wrapping of instruments into a web service; the composition of Web Services, which is modeled as a planning problem, and; the design of an online laboratory brokerage system, which we dealt with in a former article. We also discuss some issues related to business logic and policy in a particular sector, such as tele-learning and network-supported research via information technologies.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".