A roadmap for Antarctic and Southern Ocean science for the next two decades and beyond
Bibliographic record
Abstract
Abstract Antarctic and Southern Ocean science is vital to understanding natural variability, the processes that govern global change and the role of humans in the Earth and climate system. The potential for new knowledge to be gained from future Antarctic science is substantial. Therefore, the international Antarctic community came together to ‘scan the horizon’ to identify the highest priority scientific questions that researchers should aspire to answer in the next two decades and beyond. Wide consultation was a fundamental principle for the development of a collective, international view of the most important future directions in Antarctic science. From the many possibilities, the horizon scan identified 80 key scientific questions through structured debate, discussion, revision and voting. Questions were clustered into seven topics: i) Antarctic atmosphere and global connections, ii) Southern Ocean and sea ice in a warming world, iii) ice sheet and sea level, iv) the dynamic Earth, v) life on the precipice, vi) near-Earth space and beyond, and vii) human presence in Antarctica. Answering the questions identified by the horizon scan will require innovative experimental designs, novel applications of technology, invention of next-generation field and laboratory approaches, and expanded observing systems and networks. Unbiased, non-contaminating procedures will be required to retrieve the requisite air, biota, sediment, rock, ice and water samples. Sustained year-round access to Antarctica and the Southern Ocean will be essential to increase winter-time measurements. Improved models are needed that represent Antarctica and the Southern Ocean in the Earth System, and provide predictions at spatial and temporal resolutions useful for decision making. A co-ordinated portfolio of cross-disciplinary science, based on new models of international collaboration, will be essential as no scientist, programme or nation can realize these aspirations alone.
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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 | 0.023 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.059 | 0.019 |
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".