Arctic Freshwater Synthesis: Introduction
Bibliographic record
Abstract
Abstract In response to a joint request from the World Climate Research Program's Climate and Cryosphere Project, the International Arctic Science Committee, and the Arctic Council's Arctic Monitoring and Assessment Program, an updated scientific assessment has been conducted of the Arctic Freshwater System, entitled the Arctic Freshwater Synthesis (AFS). The major reason for joint request was an increasing concern that changes to the Arctic Freshwater System have produced, and could produce even greater, changes to biogeophysical and socioeconomic systems of special importance to northern residents and also produce extra‐Arctic climatic effects that will have global consequences. Hence, the key objective of the AFS was to produce an updated, comprehensive, and integrated review of the structure and function of the entire Arctic Freshwater System. The AFS was organized around six key thematic areas: atmosphere, oceans, terrestrial hydrology, terrestrial ecology, resources and modeling, and the review of each coauthored by an international group of scientists and published as separate articles in this special section of Journal of Geophysical Research: Biogeosciences. This Introduction reviews the motivations for, and foci of, previous studies of the Arctic Freshwater System, discusses criteria used to define the domain of the Arctic Freshwater System, and details key characteristics of the definition adopted for the AFS.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.010 |
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".