Observing System Simulation Experiments and Adjoint Sensitivity Analysis: Methods for Observational Programs in the Arctic Ocean
Bibliographic record
Abstract
Over recent decades, the Arctic Ocean (AO) has experienced profound climate changes. To study these climate changes, several regional observational programs have been started. Because of complicated logistics and remoteness, in situ observations in the AO are extremely expensive. Therefore, an efficient ocean observational system in the AO is critical to understand environmental changes in the Arctic. Observing System Simulation Experiments (OSSEs) and Adjoint Sensitivity Analysis (ASA) are powerful tools that could be used in the optimization of existing and incoming observational programs in the AO. These optimal planning tools recommended by the Study of Environmental Arctic Change (SEARCH) implementation plan, and widely used in atmospheric research, are still rarely implemented in physical and biological oceanography. We provide several examples of how the OSSE and ASA can be used to optimize the locations of high frequency radars and biological tracer surveys and leveraged toward creating an inexpensive drifter observational program capable of providing sufficient information to reconstruct the circulation in the northern Bering, Chukchi, and southern Beaufort Seas.
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How this classification was reachedexpand
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 | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".