OGC Sensor Web Enablement compliance for Ocean Networks Canada scalar data
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 Digital Infrastructure group at Ocean Networks Canada (ONC) is in charge of the development and maintenance of the Organization's Data Management and Archiving System (DMAS), also referred to as “Oceans 2.0”. The group has been successful in setting up a software system that acquires data from large sensor networks, archives them and makes them available to a varied audience of scientists, the public as wells as government and non-governmental agencies. Oceans 2.0 relies on its Service-Oriented Architecture to acquire data and has extended it to support data distribution to a wider range of customers using web services. More recently following a funding opportunity with CANARIE Inc. to deliver portable, re-usable middleware, OGC SWE-compliant web services were implemented. The new services offer the ability to OGC-ready clients to obtain ONC scalar data in a self-descriptive and effective way.
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 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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