Sea ice biota: Excerpts from the State of the Arctic Marine Biodiversity Report by the Sea Ice Biota Expert Network/CBMP
Bibliographic record
Abstract
Sea ice is an important Arctic habitat that supports a high diversity of species—with over 1276 protist taxa alone. Multi-year sea ice is being replaced by first-year ice and open water, which will cause shifts in ice algal communities with cascading effects on the ice-associated ecosystem. Documentation of ice biota composition, abundance and natural variability is critical for evaluating responses to the decline in Arctic sea ice. The Sea-ice Biota Expert Network, therefore, aggregated and reviewed data on status and trends of ice-associated Bacteria, Archaea, microalgae, meiofauna, and under-ice macrofauna Focal Ecosystem Components (FECs) across eight Arctic Marine Areas as well as current monitoring. Sea ice biota monitoring has occurred most frequently in the central Arctic, Svalbard area, Barrow (Alaska) and the Canadian Arctic, with recent sites in northern Greenland. Sea ice algal community structure has possibly changed in the central Arctic between the 1980s and 2010s, and ice-amphipod abundance and biomass have declined in the Svalbard area since the 1980s. Consistent monitoring protocols, equipment and methodology should be implemented. The presentation also evaluates dominant drivers of observed trends, and knowledge and monitoring gaps.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.015 |
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".