The SURA Coastal Ocean Observing and Prediction Program (SCOOP) Service-Oriented Architecture
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.
Bibliographic record
Abstract
The Southeastern Universities Research Association (SURA) Coastal Ocean Observing and Prediction Program (SCOOP) is a multi-institution collaboration whose partners are working to implement a modular, distributed system for real-time prediction and visualization of the impacts of extreme atmospheric events, including storm surge and wind-driven waves. SCOOP Program partners are developing an interoperable network of modularized components (numerical models, information catalogs, distributed archives, computing resources and network infrastructure) linked by standardized interfaces. This service-oriented architecture (SOA) is emerging as a prototype open access, distributed virtual laboratory for oceanographic research and coastal applications. The SOA approach allows data integration from multiple platforms and enables the exchange of resources, tools, and ideas among a virtual community. The SOA framework consists of five layers: (1) a user interface; (2) an application and tools layer; (3) a management layer; (4) a resource access layer; and (5) physical resources all linked by cross-cutting services. The SOA layer components support several different use cases because they can be configured into a variety of workflows
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it