How to link science and policy for the environmental protection of the Antarctic continent ?
Bibliographic record
Abstract
Antarctica is a continent dedicated to peace and science since the signature of the Antarctic Treaty in 1959. However, an elaborated environmental protection for the continent only dates from the Protocol on Environmental Protection, an annex which was signed in 1991. This Protocol includes 6 Annexes regulating the Environmental Impact Assessments and permits, the waste handling, the area and species protection, etc. During Annual meetings, the environmental questions are discussed between Parties, Observers and Experts, on the basis of the best possible scientific evidences. The scientists’ role is important, and there are organisations (e.g. SCAR) and initiatives (e.g. Antarctic Environments Portal, https://environments.aq/) that aims to strengthen the link between scientists and policy- makers. A better communication of policy priorities would help scientists to better contribute with policy-relevant data, and to participate to the environmental protection.
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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 | 0.055 | 0.140 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.017 | 0.021 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.029 | 0.064 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.022 | 0.018 |
| Insufficient payload (model declined to judge) | 0.037 | 0.017 |
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".