Remote visualisation of Labrador convection in large oceanic datasets
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
Abstract The oceans relinquish O(1PW) of heat into the atmosphere at high latitudes, the lion's share of which originates in localised ‘hotspots’ of violent convective mixing, but despite their small horizontal scale—O(10–100km)—these features may penetrate deeply into the thermocline and are vital in maintaining the Atlantic Meridional Overturning Circulation (MOC). Accurate modelling of the MOC, therefore, requires a large‐scale numerical model with very fine resolution. The global high‐resolution ocean model, Ocean Circulation Climate Advanced Model (OCCAM) has been developed and run at the Southampton Oceanography Centre (SOC) for many years. It was configured to resolve the energetic scales of oceanic motions, and its output is stored at the Manchester Supercomputer Centre. Although this community resource represents a treasure trove of potential new insights into the nature of the world ocean, it remains relatively unexploited for a number of reasons, not the least of which is its sheer size. A system being developed at SOC under the auspices of the Grid for Ocean Diagnostics, Interactive Visualisation and Analysis (GODIVA) project makes the remote visualisation of very large volumes of data on modest hardware (e.g. a laptop with no special graphics capability) a present reality. The GODIVA system is enabling the unresolved question of oceanic convection and its relationship to large‐scale flows to be investigated; a question that lies at the heart of many current climate change issues. In this article, one aspect of the GODIVA is presented, and used to locate and visualise regions of convective mixing in the OCCAM Labrador Sea. Copyright © 2006 Royal Meteorological Society
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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 | 0.002 |
| 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) | 0.001 | 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