The current status of the real-time <i>in situ</i> Global Ocean Observing System for operational oceanography
Bibliographic record
Abstract
The GODAE-OceanView collection of papers primarily concerns the development of ocean data-assimilation models for operational oceanography. However, these models cannot function without a secure supply of in situ ocean data in near real-time. Several projects and programmes supply such data. The purpose of this paper is to review these data sources and describe the history, present status, future and robustness of these programmes. The conclusion is that though challenges continue with some components of the Global Ocean Observing System, overall the system continues to evolve and improve. The data are available in real-time to drive assimilation models, and expectations are increasing for more observational data. The prospects for the next 10 years seem to be good. All of the systems are evolving and there is little doubt that the Global Ocean Observing System will look different 10 years from now as new technologies emerge and capabilities improve.
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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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".