Causes and consequences of Southern Ocean change: the IPCC SROCC assessment
Bibliographic record
Abstract
Climate change in the polar regions exerts a profound influence both locally and over all of our planet. Physical and ecosystem changes influence societies and economies, via factors that include food provision, transport and access to non-renewable resources. Sea level, global climate and potentially mid-latitude weather are influenced by the changing polar regions, through coupled feedback processes, sea ice changes and the melting of snow and land-based ice sheets and glaciers. Reflecting this importance, the IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) features a chapter highlighting past, ongoing and future change in the polar regions, the impacts of these changes, and the possible options for response. The role of the polar oceans, both in determining the changes and impacts in the polar regions and in structuring the global influence, is an important component of this chapter. With emphasis on the Southern Ocean and through comparison with the Arctic, this talk will outline key findings from the polar regions chapter of SROCC. It will synthesise the latest information on the rates, patterns and causes of changes in sea ice, ocean circulation and properties. It will assess cryospheric driving of ocean change from ice sheets, ice shelves and glaciers, and the role of the oceans in determining the past and future evolutions of polar land-based ice. The implications of these changes for climate, ecosystems, sea level and the global system will be outlined.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".