Potential impacts of sea ice and ship traffic change to caribou sea ice crossing areas surrounding King William Island, Nunavut, Canada
Bibliographic record
Abstract
Caribou (Rangifer tarandus, tuktuit in Inuktitut) use sea ice to facilitate movements that fulfill their ecological needs.Ship traffic is growing in the Kitikmeot region of Nunavut, and ice-strengthened ships can disrupt sea ice by breaking it apart.This project explored priorities identified by community members in Uqsuqtuuq (Gjoa Haven, NU) concerning changes in sea ice and ship traffic in caribou crossing areas surrounding King William Island.Using Canadian Ice Service ice charts and Canadian Coast Guard ship traffic data, the timing of freeze-up, break-up and ship transit was assessed for five caribou crossing areas.Preliminary results were discussed in workshops in Uqsuqtuuq in September 2018, and Inuit knowledge guided methods and analyses in this thesis.Despite a large interannual variability in sea ice conditions, the timing of ship movement was independent of local conditions.In the future, longer open water seasons and shifting freeze-up and break-up timing may intensify interactions between sea ice and ship transit creating challenges for caribou movement.
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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 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".