Stratification in the Canadian Arctic Archipelago’s Kitikmeot Sea: Biological and geochemical consequences
Bibliographic record
Abstract
The Kitikmeot Sea Science Study (K3S) began in 2014. It provides the Canadian High Arctic Research Station with a scientific basis for carrying out integrated, long-term ecological monitoring and research in the Kitikmeot Sea. K3S involves strong partnerships with marine and terrestrial research collaborators in the Kitikmeot. The K3S has three focus areas: 1) the Pacific-origin estuarine through-flow, which sets the oceanographic structure of the region; 2) the origin and pathways of freshwater that flows into the sea, which influences nutrient balances and stratification; and 3) biological communities that are influenced by tides. The K3S uses oceanographic and marine biological investigation tools aboard the R/V Martin Bergmann. It also maintains year-round sub-surface oceanographic moorings. Findings from K3S studies during 2014–2017 show the unique nature of the Kitikmeot Sea. Tidal mixing within the region’s many narrow, shallow straits is an important finding. This mixing brings nutrients to the surface, which supports the entire marine food-web. Further study of the Kitikmeot Sea aims to understand the connectivity of the region’s marine ecosystem and how it functions. This information will complement indigenous knowledge and is useful to northern communities. These communities depend on their marine food-webs for fish and seals and on the sea ice for travel. K3S results are beginning to provide a scientific basis for why the region’s tidal straits have high biological production and dangerous, thin ice. The K3S will continue to collaborate with community partners to investigate these themes throughout the Kitikmeot.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".