GODAE OceanView Inter-comparison for the Australian Region
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
This paper compares the performance of short-range operational ocean forecasts, using ‘observational space’ metrics developed under GODAE OceanView (GOV). Best estimates (behind the real-time analysis) and forecasts are inter-compared for the Australian region (0-50S, 90-180E) for 2013. Systems considered include those developed in Australia, France, Canada, United Kingdom and USA. Each system is compared to observations of along-track sea level anomaly, sea surface temperature observations from surface drifters and sub-surface Argo profiles of temperature and salinity. The UK operational system generally has the smallest errors for sea surface temperature and sea level anomaly for the Australian region. However, the French systems outperform others in sub-surface temperature and salinity for the region. Of the two products provided by the Australian centre, an ensemble based approach is found to perform better than the deterministic system, having higher skill and lower root mean square errors. Some of the ‘better’ results of systems can be attributed in part to the lack of independence of the reference observations; however the study does demonstrate the feasibility and robustness of GOV global ocean inter-comparison efforts for regional applications.
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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 | 0.001 | 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 | 0.000 | 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